Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression.
Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.
The study of systems which respond disproportionately (nonlinearly) to initial conditions or perturbing stimuli. Nonlinear systems may exhibit "chaos" which is classically characterized as sensitive dependence on initial conditions. Chaotic systems, while distinguished from more ordered periodic systems, are not random. When their behavior over time is appropriately displayed (in "phase space"), constraints are evident which are described by "strange attractors". Phase space representations of chaotic systems, or strange attractors, usually reveal fractal (FRACTALS) self-similarity across time scales. Natural, including biological, systems often display nonlinear dynamics and chaos.
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.
Computer-based representation of physical systems and phenomena such as chemical processes.
Application of statistical procedures to analyze specific observed or assumed facts from a particular study.
A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.
The production of offspring by selective mating or HYBRIDIZATION, GENETIC in animals or plants.
Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.
The application of STATISTICS to biological systems and organisms involving the retrieval or collection, analysis, reduction, and interpretation of qualitative and quantitative data.
Studies in which variables relating to an individual or group of individuals are assessed over a period of time.
Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.
Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.
Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.
A principle of estimation in which the estimates of a set of parameters in a statistical model are those quantities minimizing the sum of squared differences between the observed values of a dependent variable and the values predicted by the model.
Theoretical representations that simulate the behavior or activity of the neurological system, processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment.
Genetic loci associated with a QUANTITATIVE TRAIT.
The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.
Elements of limited time intervals, contributing to particular results or situations.
A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space.
A characteristic showing quantitative inheritance such as SKIN PIGMENTATION in humans. (From A Dictionary of Genetics, 4th ed)
Non-invasive method of demonstrating internal anatomy based on the principle that atomic nuclei in a strong magnetic field absorb pulses of radiofrequency energy and emit them as radiowaves which can be reconstructed into computerized images. The concept includes proton spin tomographic techniques.
Continuous frequency distribution of infinite range. Its properties are as follows: 1, continuous, symmetrical distribution with both tails extending to infinity; 2, arithmetic mean, mode, and median identical; and 3, shape completely determined by the mean and standard deviation.
Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time.
Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.
The use of statistical and mathematical methods to analyze biological observations and phenomena.
Studies in which subsets of a defined population are identified. These groups may or may not be exposed to factors hypothesized to influence the probability of the occurrence of a particular disease or other outcome. Cohorts are defined populations which, as a whole, are followed in an attempt to determine distinguishing subgroup characteristics.
An aspect of personal behavior or lifestyle, environmental exposure, or inborn or inherited characteristic, which, on the basis of epidemiologic evidence, is known to be associated with a health-related condition considered important to prevent.
Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time.
A set of techniques used when variation in several variables has to be studied simultaneously. In statistics, multivariate analysis is interpreted as any analytic method that allows simultaneous study of two or more dependent variables.
Mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components.
A technique of inputting two-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer.
Predetermined sets of questions used to collect data - clinical data, social status, occupational group, etc. The term is often applied to a self-completed survey instrument.
A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.
Infections or infestations with parasitic organisms. The infestation may be experimental or veterinary.
The science and art of collecting, summarizing, and analyzing data that are subject to random variation. The term is also applied to the data themselves and to the summarization of the data.
Imaging techniques used to colocalize sites of brain functions or physiological activity with brain structures.
In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993)
A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable.
The genetic constitution of the individual, comprising the ALLELES present at each GENETIC LOCUS.
The part of CENTRAL NERVOUS SYSTEM that is contained within the skull (CRANIUM). Arising from the NEURAL TUBE, the embryonic brain is comprised of three major parts including PROSENCEPHALON (the forebrain); MESENCEPHALON (the midbrain); and RHOMBENCEPHALON (the hindbrain). The developed brain consists of CEREBRUM; CEREBELLUM; and other structures in the BRAIN STEM.
Sequential operating programs and data which instruct the functioning of a digital computer.
The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.
The comparison of the quantity of meaningful data to the irrelevant or incorrect data.
The outward appearance of the individual. It is the product of interactions between genes, and between the GENOTYPE and the environment.
Maleness or femaleness as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or effect of a circumstance. It is used with human or animal concepts but should be differentiated from SEX CHARACTERISTICS, anatomical or physiological manifestations of sex, and from SEX DISTRIBUTION, the number of males and females in given circumstances.
Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING.
An indicator of body density as determined by the relationship of BODY WEIGHT to BODY HEIGHT. BMI=weight (kg)/height squared (m2). BMI correlates with body fat (ADIPOSE TISSUE). Their relationship varies with age and gender. For adults, BMI falls into these categories: below 18.5 (underweight); 18.5-24.9 (normal); 25.0-29.9 (overweight); 30.0 and above (obese). (National Center for Health Statistics, Centers for Disease Control and Prevention)
The actual costs of providing services related to the delivery of health care, including the costs of procedures, therapies, and medications. It is differentiated from HEALTH EXPENDITURES, which refers to the amount of money paid for the services, and from fees, which refers to the amount charged, regardless of cost.
The state of the ATMOSPHERE over minutes to months.
Divisions of the year according to some regularly recurrent phenomena usually astronomical or climatic. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)
Genotypic differences observed among individuals in a population.
A hereditary disease of the hip joints in dogs. Signs of the disease may be evident any time after 4 weeks of age.
The presence of contaminants or pollutant substances in the air (AIR POLLUTANTS) that interfere with human health or welfare, or produce other harmful environmental effects. The substances may include GASES; PARTICULATE MATTER; or volatile ORGANIC CHEMICALS.
A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.
Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor.
Studies which start with the identification of persons with a disease of interest and a control (comparison, referent) group without the disease. The relationship of an attribute to the disease is examined by comparing diseased and non-diseased persons with regard to the frequency or levels of the attribute in each group.
Any substance in the air which could, if present in high enough concentration, harm humans, animals, vegetation or material. Substances include GASES; PARTICULATE MATTER; and volatile ORGANIC CHEMICALS.
Studies used to test etiologic hypotheses in which inferences about an exposure to putative causal factors are derived from data relating to characteristics of persons under study or to events or experiences in their past. The essential feature is that some of the persons under study have the disease or outcome of interest and their characteristics are compared with those of unaffected persons.
Observation of a population for a sufficient number of persons over a sufficient number of years to generate incidence or mortality rates subsequent to the selection of the study group.
The status during which female mammals carry their developing young (EMBRYOS or FETUSES) in utero before birth, beginning from FERTILIZATION to BIRTH.
The number of units (persons, animals, patients, specified circumstances, etc.) in a population to be studied. The sample size should be big enough to have a high likelihood of detecting a true difference between two groups. (From Wassertheil-Smoller, Biostatistics and Epidemiology, 1990, p95)
The exposure to potentially harmful chemical, physical, or biological agents in the environment or to environmental factors that may include ionizing radiation, pathogenic organisms, or toxic chemicals.
A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly.
A large or important municipality of a country, usually a major metropolitan center.
The gradual irreversible changes in structure and function of an organism that occur as a result of the passage of time.
Computer-assisted interpretation and analysis of various mathematical functions related to a particular problem.
A stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system.
The external elements and conditions which surround, influence, and affect the life and development of an organism or population.
Domesticated bovine animals of the genus Bos, usually kept on a farm or ranch and used for the production of meat or dairy products or for heavy labor.
Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease.
Levels within a diagnostic group which are established by various measurement criteria applied to the seriousness of a patient's disorder.
A range of values for a variable of interest, e.g., a rate, constructed so that this range has a specified probability of including the true value of the variable.
Any visible result of a procedure which is caused by the procedure itself and not by the entity being analyzed. Common examples include histological structures introduced by tissue processing, radiographic images of structures that are not naturally present in living tissue, and products of chemical reactions that occur during analysis.
Evaluation undertaken to assess the results or consequences of management and procedures used in combating disease in order to determine the efficacy, effectiveness, safety, and practicability of these interventions in individual cases or series.
A generic concept reflecting concern with the modification and enhancement of life attributes, e.g., physical, political, moral and social environment; the overall condition of a human life.
Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease.
Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed)
The analysis of a sequence such as a region of a chromosome, a haplotype, a gene, or an allele for its involvement in controlling the phenotype of a specific trait, metabolic pathway, or disease.
A status with BODY WEIGHT that is grossly above the acceptable or desirable weight, usually due to accumulation of excess FATS in the body. The standards may vary with age, sex, genetic or cultural background. In the BODY MASS INDEX, a BMI greater than 30.0 kg/m2 is considered obese, and a BMI greater than 40.0 kg/m2 is considered morbidly obese (MORBID OBESITY).
An analysis comparing the allele frequencies of all available (or a whole GENOME representative set of) polymorphic markers in unrelated patients with a specific symptom or disease condition, and those of healthy controls to identify markers associated with a specific disease or condition.
A form of gene interaction whereby the expression of one gene interferes with or masks the expression of a different gene or genes. Genes whose expression interferes with or masks the effects of other genes are said to be epistatic to the effected genes. Genes whose expression is affected (blocked or masked) are hypostatic to the interfering genes.
A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.
An infant during the first month after birth.
The deductive study of shape, quantity, and dependence. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)
Review of claims by insurance companies to determine liability and amount of payment for various services. The review may also include determination of eligibility of the claimant or beneficiary or of the provider of the benefit; determination that the benefit is covered or not payable under another policy; or determination that the service was necessary and of reasonable cost and quality.
The longterm manifestations of WEATHER. (McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)
Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity.
The monitoring of the level of toxins, chemical pollutants, microbial contaminants, or other harmful substances in the environment (soil, air, and water), workplace, or in the bodies of people and animals present in that environment.
Social and economic factors that characterize the individual or group within the social structure.
The range or frequency distribution of a measurement in a population (of organisms, organs or things) that has not been selected for the presence of disease or abnormality.
A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.
Persons living in the United States having origins in any of the black groups of Africa.
The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms.
Individuals whose ancestral origins are in the continent of Europe.
Any method used for determining the location of and relative distances between genes on a chromosome.
Tests designed to assess neurological function associated with certain behaviors. They are used in diagnosing brain dysfunction or damage and central nervous system disorders or injury.
A phenotypically recognizable genetic trait which can be used to identify a genetic locus, a linkage group, or a recombination event.
Parliamentary democracy located between France on the northeast and Portugual on the west and bordered by the Atlantic Ocean and the Mediterranean Sea.
Measurable and quantifiable biological parameters (e.g., specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, environmental exposure and its effects, disease diagnosis, metabolic processes, substance abuse, pregnancy, cell line development, epidemiologic studies, etc.
The mass or quantity of heaviness of an individual at BIRTH. It is expressed by units of pounds or kilograms.
A status with BODY WEIGHT that is above certain standard of acceptable or desirable weight. In the scale of BODY MASS INDEX, overweight is defined as having a BMI of 25.0-29.9 kg/m2. Overweight may or may not be due to increases in body fat (ADIPOSE TISSUE), hence overweight does not equal "over fat".
Investigative technique commonly used during ELECTROENCEPHALOGRAPHY in which a series of bright light flashes or visual patterns are used to elicit brain activity.
The total number of cases of a given disease in a specified population at a designated time. It is differentiated from INCIDENCE, which refers to the number of new cases in the population at a given time.
Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.
Regular course of eating and drinking adopted by a person or animal.
Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.
Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language.
Intellectual or mental process whereby an organism obtains knowledge.
The total area or space visible in a person's peripheral vision with the eye looking straightforward.
Disturbances in mental processes related to learning, thinking, reasoning, and judgment.
The coordination of a sensory or ideational (cognitive) process and a motor activity.
A country spanning from central Asia to the Pacific Ocean.
The technique that deals with the measurement of the size, weight, and proportions of the human or other primate body.
Nonrandom association of linked genes. This is the tendency of the alleles of two separate but already linked loci to be found together more frequently than would be expected by chance alone.
The physical activity of a human or an animal as a behavioral phenomenon.
The presence of co-existing or additional diseases with reference to an initial diagnosis or with reference to the index condition that is the subject of study. Comorbidity may affect the ability of affected individuals to function and also their survival; it may be used as a prognostic indicator for length of hospital stay, cost factors, and outcome or survival.
The time from the onset of a stimulus until a response is observed.
In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.
Persons or animals having at least one parent in common. (American College Dictionary, 3d ed)
A food group comprised of EDIBLE PLANTS or their parts.
Particles of any solid substance, generally under 30 microns in size, often noted as PM30. There is special concern with PM1 which can get down to PULMONARY ALVEOLI and induce MACROPHAGE ACTIVATION and PHAGOCYTOSIS leading to FOREIGN BODY REACTION and LUNG DISEASES.
The consequences of exposing the FETUS in utero to certain factors, such as NUTRITION PHYSIOLOGICAL PHENOMENA; PHYSIOLOGICAL STRESS; DRUGS; RADIATION; and other physical or chemical factors. These consequences are observed later in the offspring after BIRTH.
An imaging method using LASERS that is used for mapping subsurface structure. When a reflective site in the sample is at the same optical path length (coherence) as the reference mirror, the detector observes interference fringes.
A functional system which includes the organisms of a natural community together with their environment. (McGraw Hill Dictionary of Scientific and Technical Terms, 4th ed)
The visually perceived property of objects created by absorption or reflection of specific wavelengths of light.
The qualitative or quantitative estimation of the likelihood of adverse effects that may result from exposure to specified health hazards or from the absence of beneficial influences. (Last, Dictionary of Epidemiology, 1988)
Method of measuring and mapping the scope of vision, from central to peripheral of each eye.
Those characteristics that distinguish one SEX from the other. The primary sex characteristics are the OVARIES and TESTES and their related hormones. Secondary sex characteristics are those which are masculine or feminine but not directly related to reproduction.
Elements of residence that characterize a population. They are applicable in determining need for and utilization of health services.
A class of statistical methods applicable to a large set of probability distributions used to test for correlation, location, independence, etc. In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. An important class of nonparametric tests employs the ordinal properties of the data. Another class of tests uses information about whether an observation is above or below some fixed value such as the median, and a third class is based on the frequency of the occurrence of runs in the data. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed, p1284; Corsini, Concise Encyclopedia of Psychology, 1987, p764-5)
In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed)
The science of breeding, feeding and care of domestic animals; includes housing and nutrition.
A measure of the amount of WATER VAPOR in the air.
The number of offspring produced at one birth by a viviparous animal.
The genetic constitution of individuals with respect to one member of a pair of allelic genes, or sets of genes that are closely linked and tend to be inherited together such as those of the MAJOR HISTOCOMPATIBILITY COMPLEX.
Inhaling and exhaling the smoke of burning TOBACCO.
An element with atomic symbol O, atomic number 8, and atomic weight [15.99903; 15.99977]. It is the most abundant element on earth and essential for respiration.
The confinement of a patient in a hospital.
Deliberate breeding of two different individuals that results in offspring that carry part of the genetic material of each parent. The parent organisms must be genetically compatible and may be from different varieties or closely related species.
Number of individuals in a population relative to space.
A species of SWINE, in the family Suidae, comprising a number of subspecies including the domestic pig Sus scrofa domestica.
Theoretical representations that simulate psychological processes and/or social processes. These include the use of mathematical equations, computers, and other electronic equipment.
Depressive states usually of moderate intensity in contrast with major depression present in neurotic and psychotic disorders.
The co-inheritance of two or more non-allelic GENES due to their being located more or less closely on the same CHROMOSOME.
A latent susceptibility to disease at the genetic level, which may be activated under certain conditions.
Pathological conditions involving the CARDIOVASCULAR SYSTEM including the HEART; the BLOOD VESSELS; or the PERICARDIUM.
Any of various animals that constitute the family Suidae and comprise stout-bodied, short-legged omnivorous mammals with thick skin, usually covered with coarse bristles, a rather long mobile snout, and small tail. Included are the genera Babyrousa, Phacochoerus (wart hogs), and Sus, the latter containing the domestic pig (see SUS SCROFA).
Includes the spectrum of human immunodeficiency virus infections that range from asymptomatic seropositivity, thru AIDS-related complex (ARC), to acquired immunodeficiency syndrome (AIDS).
A group of cold-blooded, aquatic vertebrates having gills, fins, a cartilaginous or bony endoskeleton, and elongated bodies covered with scales.
The number of offspring a female has borne. It is contrasted with GRAVIDITY, which refers to the number of pregnancies, regardless of outcome.
A shiny gray element with atomic symbol As, atomic number 33, and atomic weight 75. It occurs throughout the universe, mostly in the form of metallic arsenides. Most forms are toxic. According to the Fourth Annual Report on Carcinogens (NTP 85-002, 1985), arsenic and certain arsenic compounds have been listed as known carcinogens. (From Merck Index, 11th ed)
Statistical interpretation and description of a population with reference to distribution, composition, or structure.
Physical activity which is usually regular and done with the intention of improving or maintaining PHYSICAL FITNESS or HEALTH. Contrast with PHYSICAL EXERTION which is concerned largely with the physiologic and metabolic response to energy expenditure.
The discipline studying genetic composition of populations and effects of factors such as GENETIC SELECTION, population size, MUTATION, migration, and GENETIC DRIFT on the frequencies of various GENOTYPES and PHENOTYPES using a variety of GENETIC TECHNIQUES.
Assessment of psychological variables by the application of mathematical procedures.
Research aimed at assessing the quality and effectiveness of health care as measured by the attainment of a specified end result or outcome. Measures include parameters such as improved health, lowered morbidity or mortality, and improvement of abnormal states (such as elevated blood pressure).
The level of health of the individual, group, or population as subjectively assessed by the individual or by more objective measures.
Analysis based on the mathematical function first formulated by Jean-Baptiste-Joseph Fourier in 1807. The function, known as the Fourier transform, describes the sinusoidal pattern of any fluctuating pattern in the physical world in terms of its amplitude and its phase. It has broad applications in biomedicine, e.g., analysis of the x-ray crystallography data pivotal in identifying the double helical nature of DNA and in analysis of other molecules, including viruses, and the modified back-projection algorithm universally used in computerized tomography imaging, etc. (From Segen, The Dictionary of Modern Medicine, 1992)
A method of studying a drug or procedure in which both the subjects and investigators are kept unaware of who is actually getting which specific treatment.
The number of new cases of a given disease during a given period in a specified population. It also is used for the rate at which new events occur in a defined population. It is differentiated from PREVALENCE, which refers to all cases, new or old, in the population at a given time.
The white liquid secreted by the mammary glands. It contains proteins, sugar, lipids, vitamins, and minerals.
PRESSURE of the BLOOD on the ARTERIES and other BLOOD VESSELS.
Permanent deprivation of breast milk and commencement of nourishment with other food. (From Stedman, 25th ed)
Area of the OCCIPITAL LOBE concerned with the processing of visual information relayed via VISUAL PATHWAYS.
The science dealing with the earth and its life, especially the description of land, sea, and air and the distribution of plant and animal life, including humanity and human industries with reference to the mutual relations of these elements. (From Webster, 3d ed)
The physical measurements of a body.
The study of chance processes or the relative frequency characterizing a chance process.
A severe emotional disorder of psychotic depth characteristically marked by a retreat from reality with delusion formation, HALLUCINATIONS, emotional disharmony, and regressive behavior.
The amount that a health care institution or organization pays for its drugs. It is one component of the final price that is charged to the consumer (FEES, PHARMACEUTICAL or PRESCRIPTION FEES).
The variety of all native living organisms and their various forms and interrelationships.
The prediction or projection of the nature of future problems or existing conditions based upon the extrapolation or interpretation of existing scientific data or by the application of scientific methodology.
Increase in BODY WEIGHT over existing weight.
Persons who receive ambulatory care at an outpatient department or clinic without room and board being provided.
A multistage process that includes cloning, physical mapping, subcloning, sequencing, and information analysis of an RNA SEQUENCE.
The edible portions of any animal used for food including domestic mammals (the major ones being cattle, swine, and sheep) along with poultry, fish, shellfish, and game.
The fleshy or dry ripened ovary of a plant, enclosing the seed or seeds.
All deaths reported in a given population.
Groups of individuals whose putative ancestry is from native continental populations based on similarities in physical appearance.
The systematic study of the complete DNA sequences (GENOME) of organisms.
Variant forms of the same gene, occupying the same locus on homologous CHROMOSOMES, and governing the variants in production of the same gene product.
The personal cost of acute or chronic disease. The cost to the patient may be an economic, social, or psychological cost or personal loss to self, family, or immediate community. The cost of illness may be reflected in absenteeism, productivity, response to treatment, peace of mind, or QUALITY OF LIFE. It differs from HEALTH CARE COSTS, meaning the societal cost of providing services related to the delivery of health care, rather than personal impact on individuals.
The inhabitants of a city or town, including metropolitan areas and suburban areas.
A social group consisting of parents or parent substitutes and children.
Use of sound to elicit a response in the nervous system.
Hospital department responsible for the administration and provision of immediate medical or surgical care to the emergency patient.
Living facilities for humans.
Persons who have experienced a prolonged survival after serious disease or who continue to live with a usually life-threatening condition as well as family members, significant others, or individuals surviving traumatic life events.
A country in western Europe bordered by the Atlantic Ocean, the English Channel, the Mediterranean Sea, and the countries of Belgium, Germany, Italy, Spain, Switzerland, the principalities of Andorra and Monaco, and by the duchy of Luxembourg. Its capital is Paris.
A graphic means for assessing the ability of a screening test to discriminate between healthy and diseased persons; may also be used in other studies, e.g., distinguishing stimuli responses as to a faint stimuli or nonstimuli.
The basic cellular units of nervous tissue. Each neuron consists of a body, an axon, and dendrites. Their purpose is to receive, conduct, and transmit impulses in the NERVOUS SYSTEM.
The total process by which organisms produce offspring. (Stedman, 25th ed)
Ongoing scrutiny of a population (general population, study population, target population, etc.), generally using methods distinguished by their practicability, uniformity, and frequently their rapidity, rather than by complete accuracy.
Neurons of the innermost layer of the retina, the internal plexiform layer. They are of variable sizes and shapes, and their axons project via the OPTIC NERVE to the brain. A small subset of these cells act as photoreceptors with projections to the SUPRACHIASMATIC NUCLEUS, the center for regulating CIRCADIAN RHYTHM.
The exposure to potentially harmful chemical, physical, or biological agents that occurs as a result of one's occupation.
Stress wherein emotional factors predominate.
The status of health in urban populations.

## Capture-recapture models including covariate effects. (2/13525)

Capture-recapture methods are used to estimate the incidence of a disease, using a multiple-source registry. Usually, log-linear methods are used to estimate population size, assuming that not all sources of notification are dependent. Where there are categorical covariates, a stratified analysis can be performed. The multinomial logit model has occasionally been used. In this paper, the authors compare log-linear and logit models with and without covariates, and use simulated data to compare estimates from different models. The crude estimate of population size is biased when the sources are not independent. Analyses adjusting for covariates produce less biased estimates. In the absence of covariates, or where all covariates are categorical, the log-linear model and the logit model are equivalent. The log-linear model cannot include continuous variables. To minimize potential bias in estimating incidence, covariates should be included in the design and analysis of multiple-source disease registries.  (+info)

## The impact of a multidisciplinary approach on caring for ventilator-dependent patients. (3/13525)

OBJECTIVE: To determine the clinical and financial outcomes of a highly structured multidisciplinary care model for patients in an intensive care unit (ICU) who require prolonged mechanical ventilation. The structured model outcomes (protocol group) are compared with the preprotocol outcomes. DESIGN: Descriptive study with financial analysis. SETTING: A twelve-bed medical-surgical ICU in a non-teaching tertiary referral center in Ogden, Utah. STUDY PARTICIPANTS: During a 54 month period, 469 consecutive intensive care patients requiring mechanical ventilation for longer than 72 hours who did not meet exclusion criteria were studied. INTERVENTIONS: A multidisciplinary team was formed to coordinate the care of ventilator-dependent patients. Care was integrated by daily collaborative bedside rounds, monthly meetings, and implementation of numerous guidelines and protocols. Patients were followed from the time of ICU admission until the day of hospital discharge. MAIN OUTCOME MEASURES: Patients were assigned APACHE II scores on admission to the ICU, and were divided into eight diagnostic categories. ICU length of stay, hospital length of stay, costs, charges, reimbursement, and in-hospital mortality were measured. RESULTS: Mortality in the preprotocol and protocol group, after adjustment for APACHE II scores, remained statistically unchanged (21-23%). After we implemented the new care model, we demonstrated significant decreases in the mean survivor's ICU length of stay (19.8 days to 14.7 days, P= 0.001), hospital length of stay (34.6 days to 25.9 days, P=0.001), charges (US$102500 to US$78500, P=0.001), and costs (US$71900 to US$58000, P=0.001). CONCLUSIONS: Implementation of a structured multidisciplinary care model to care for a heterogeneous population of ventilator-dependent ICU patients was associated with significant reductions in ICU and hospital lengths of stay, charges, and costs. Mortality rates were unaffected.  (+info)

## Nonlinear tension summation of different combinations of motor units in the anesthetized cat peroneus longus muscle. (4/13525)

The purpose of this study was to examine the linearity of summation of the forces produced by the stimulation of different combinations of type identified motor units (MUs) in the cat peroneus longus muscle (PL) under isometric conditions. The muscle was fixed at its twitch optimal length, and the tension produced by the single MU was recorded during 24- and 72-Hz stimulation. The summation analysis was first carried out for MUs belonging to the same functional group, and then different combinations of fast fatigable (FF) MUs were added to the nonfatigable slow (S) and fatigue resistant (FR) group. The tension resulting from the combined stimulation of increasing numbers of MUs (measured tension) was evaluated and compared with the linearly predicted value, calculated by adding algebraically the tension produced by the individual MUs assembled in the combination (calculated tension). Tension summation displayed deviations from linearity. S and FR MUs mainly showed marked more than linear summation; FF MUs yielded either more or less than linear summation; and, when the FF units were recruited after the S and FR MUs, less than linear summation always occurred. The magnitude of the nonlinear summation appeared stimulus frequency dependent for the fatigable FF and FI group. The relationship between measured tension and calculated tension for each MU combination was examined, and linear regression lines were fitted to each set of data. The high correlation coefficients and the different slope values for the different MU-type combinations suggested that the nonlinear summation was MU-type specific. The mechanisms of nonlinear summations are discussed by considering the consequences of internal shortening and thus the mechanical interactions among MUs and shifts in muscle fiber length to a more or less advantageous portion of single MU length-tension curves.  (+info)

## Short-latency vergence eye movements induced by radial optic flow in humans: dependence on ambient vergence level. (5/13525)

Radial patterns of optic flow, such as those experienced by moving observers who look in the direction of heading, evoke vergence eye movements at short latency. We have investigated the dependence of these responses on the ambient vergence level. Human subjects faced a large tangent screen onto which two identical random-dot patterns were back-projected. A system of crossed polarizers ensured that each eye saw only one of the patterns, with mirror galvanometers to control the horizontal positions of the images and hence the vergence angle between the two eyes. After converging the subject's eyes at one of several distances ranging from 16.7 cm to infinity, both patterns were replaced with new ones (using a system of shutters and two additional projectors) so as to simulate the radial flow associated with a sudden 4% change in viewing distance with the focus of expansion/contraction imaged in or very near both foveas. Radial-flow steps induced transient vergence at latencies of 80-100 ms, expansions causing increases in convergence and contractions the converse. Based on the change in vergence 90-140 ms after the onset of the steps, responses were proportional to the preexisting vergence angle (and hence would be expected to be inversely proportional to viewing distance under normal conditions). We suggest that this property assists the observer who wants to fixate ahead while passing through a visually cluttered area (e.g., a forest) and so wants to avoid making vergence responses to the optic flow created by the nearby objects in the periphery.  (+info)

## Survival after breast cancer in Ashkenazi Jewish BRCA1 and BRCA2 mutation carriers. (6/13525)

BACKGROUND: Studies of survival following breast and ovarian cancers in BRCA1 and/or BRCA2 mutation carriers have yielded conflicting results. We undertook an analysis of a community-based study of Ashkenazi Jews to investigate the effect of three founder mutations in BRCA1 and BRCA2 on survival among patients with breast or ovarian cancer. METHODS: We collected blood samples and questionnaire data from 5318 Ashkenazi Jewish volunteers. The blood samples were tested for 185delAG (two nucleotide deletion) and 5382insC (single nucleotide insertion) mutations in BRCA1 and the 6174delT (single nucleotide deletion) mutation in BRCA2. To estimate survival differences in the affected relatives according to their BRCA1 and/or BRCA2 mutation carrier status, we devised and applied a novel extension of the kin-cohort method. RESULTS: Fifty mutation carriers reported that 58 of their first-degree relatives had been diagnosed with breast cancer and 10 with ovarian cancer; 907 noncarriers reported 979 first-degree relatives with breast cancer and 116 with ovarian cancer. Kaplan-Meier estimates of median survival after breast cancer were 16 years (95% confidence interval [CI] = 11-40) in the relatives of carriers and 18 years (95% CI = 15-22) in the relatives of noncarriers, a difference that was not statistically significant (two-sided P = .87). There was also no difference in survival times among the 126 first-degree relatives with ovarian cancer. We found no survival difference between patients with breast or ovarian cancer who were inferred carriers of BRCA1 and/or BRCA2 mutations and noncarriers. CONCLUSIONS: Carriers of BRCA1 and BRCA2 mutations appeared to have neither better nor worse survival prognosis.  (+info)

## Long-term results of GH therapy in GH-deficient children treated before 1 year of age. (7/13525)

OBJECTIVES: To evaluate the long-term effects of GH therapy in early diagnosed GH-deficient patients treated before 1 year of age. STUDY DESIGN: We studied all 59 patients (33 males) recorded by Association France-Hypophyse and treated with GH (0.50+/-0.15 IU/kg (S.D.) per week) before 1 year of age. Clinical presentation and growth parameters under GH treatment were analyzed. RESULTS: Neonatal manifestations of hypopituitarism were frequent: hypoglycemia (n=50), jaundice (n=25) and micropenis (n=17/33). Although birth length was moderately reduced (-0.9+/-1.4), growth retardation at diagnosis (5.8+/-3.8 months) was severe (-3.5+/-1.9 standard deviation scores (SDS)). Fifty patients (85%) had thyrotropin and/or corticotropin deficiency. After a mean duration of GH therapy of 8.0+/-3.6 years, change in height SDS was +3.11+/-2.06 S.D., exceeding 4 SDS in 19 patients. Only 9 patients (15%) did not reach a height of -2 S.D. for chronological age and 20 patients (34%) exceeded their target height. Pretreatment height SDS was independently associated with total catch-up growth. CONCLUSION: Conventional doses of GH allow normalization of height in patients with early GH deficiency and treatment.  (+info)

## Changes in body composition and leptin levels during growth hormone (GH) treatment in short children with various GH secretory capacities. (8/13525)

OBJECTIVE: The aim of this study was to follow changes in body composition, estimated by dual-energy X-ray absorptiometry (DXA), in relation to changes in leptin during the first year of GH therapy in order to test the hypothesis that leptin is a metabolic signal involved in the regulation of GH secretion in children. DESIGN AND METHODS: In total, 33 prepubertal children were investigated. Their mean (S.D.) chronological age at the start of GH treatment was 11.5 (1.6) years, and their mean height was -2.33 (0.38) S.D. scores (SDS). GH was administered subcutaneously at a daily dose of 0.1 (n=26) or 0.2 (n=7) IU/kg body weight. Ten children were in the Swedish National Registry for children with GH deficiency, and twenty-three children were involved in trials of GH treatment for idiopathic short stature. Spontaneous 24-h GH secretion was studied in 32 of the children. In the 24-h GH profiles, the maximum level of GH was determined and the secretion rate estimated by deconvolution analysis (GHt). Serum leptin levels were measured at the start of GH treatment and after 10 and 30 days and 3, 6 and 12 months of treatment. Body composition measurements, by DXA, were performed at baseline and 12 months after the onset of GH treatment. RESULTS: After 12 months of GH treatment, mean height increased from -2.33 to -1.73 SDS and total body fat decreased significantly by 3.0 (3.3)%. Serum leptin levels were decreased significantly at all time points studied compared with baseline. There was a significant correlation between the change in total body fat and the change in serum leptin levels during the 12 months of GH treatment, whereas the leptin concentration per unit fat mass did not change. In a multiple stepwise linear regression analysis with 12 month change in leptin levels as the dependent variable, the percentage change in fat over 12 months, the baseline fat mass (%) of body mass and GHt accounted for 24.0%, 11.5% and 12.2% of the variability respectively. CONCLUSIONS: There are significant correlations between changes in leptin and fat and endogenous GH secretion in short children with various GH secretory capacities. Leptin may be the messenger by which the adipose tissue affects hypothalamic regulation of GH secretion.  (+info)

Parasitic diseases in animals refer to infections caused by parasites, which are organisms that live on or inside a host organism and obtain nutrients at the host's expense. These parasites can be protozoa, helminths (worms), or arthropods such as ticks and fleas. Parasitic diseases in animals can have a significant impact on animal health and welfare, as well as on human health if the parasites are zoonotic (able to be transmitted from animals to humans). Examples of parasitic diseases in animals include: - Toxoplasmosis, caused by the protozoan Toxoplasma gondii, which can infect a wide range of animals including cats, dogs, livestock, and wildlife. - Roundworm infections, caused by various species of helminths such as Toxocara canis and Toxascaris leonina, which can infect dogs and cats and can be transmitted to humans. - Tapeworm infections, caused by various species of tapeworms such as Dipylidium caninum and Taenia solium, which can infect dogs, cats, and humans. - Flea-borne diseases, such as plague and typhus, which are caused by bacteria transmitted by fleas that feed on infected animals. Treatment of parasitic diseases in animals typically involves the use of antiparasitic drugs, although in some cases, prevention through vaccination or other measures may be more effective. It is important for veterinarians and animal owners to be aware of the risks of parasitic diseases in animals and to take appropriate measures to prevent and control them.

Hip dysplasia is a common orthopedic condition that affects dogs, particularly large and giant breed dogs. It is a developmental disorder that occurs when the hip joint does not form properly, leading to a malformation of the hip socket and the head of the femur (thigh bone). In dogs with hip dysplasia, the hip joint is unstable and can cause pain, lameness, and difficulty in movement. The severity of the condition can vary, ranging from mild to severe, and can be influenced by factors such as genetics, nutrition, and exercise. Diagnosis of hip dysplasia in dogs typically involves a physical examination, radiographs (X-rays) of the hip joint, and sometimes blood tests to rule out other conditions that may cause similar symptoms. Treatment options for hip dysplasia in dogs include medication to manage pain and inflammation, physical therapy, and in severe cases, surgery to correct the malformation of the hip joint.

Obesity is a medical condition characterized by an excessive accumulation of body fat, which increases the risk of various health problems. The World Health Organization (WHO) defines obesity as a body mass index (BMI) of 30 or higher, where BMI is calculated as a person's weight in kilograms divided by their height in meters squared. Obesity is a complex condition that results from a combination of genetic, environmental, and behavioral factors. It can lead to a range of health problems, including type 2 diabetes, heart disease, stroke, certain types of cancer, and respiratory problems. In the medical field, obesity is often treated through a combination of lifestyle changes, such as diet and exercise, and medical interventions, such as medications or bariatric surgery. The goal of treatment is to help individuals achieve and maintain a healthy weight, reduce their risk of health problems, and improve their overall quality of life.

In the medical field, body weight refers to the total mass of an individual's body, typically measured in kilograms (kg) or pounds (lbs). It is an important indicator of overall health and can be used to assess a person's risk for certain health conditions, such as obesity, diabetes, and heart disease. Body weight is calculated by measuring the amount of mass that a person's body contains, which includes all of the organs, tissues, bones, and fluids. It is typically measured using a scale or other weighing device, and can be influenced by factors such as age, gender, genetics, and lifestyle. Body weight can be further categorized into different types, such as body mass index (BMI), which takes into account both a person's weight and height, and waist circumference, which measures the size of a person's waist. These measures can provide additional information about a person's overall health and risk for certain conditions.

In the medical field, birth weight refers to the weight of a newborn baby at the time of delivery. It is typically measured in grams or ounces and is an important indicator of a baby's health and development. Birth weight is influenced by a variety of factors, including the mother's health, nutrition, and lifestyle, as well as the baby's genetics and gestational age. Babies who are born with a low birth weight (less than 2,500 grams or 5.5 pounds) are considered premature or small for gestational age, which can increase their risk of health problems such as respiratory distress syndrome, jaundice, and infections. On the other hand, babies who are born with a high birth weight (greater than 4,000 grams or 8.8 pounds) may be at risk for complications such as shoulder dystocia, which can lead to nerve damage or other injuries during delivery. Overall, birth weight is an important measure of a baby's health and development, and healthcare providers closely monitor it during pregnancy and delivery to ensure the best possible outcomes for both the mother and baby.

In the medical field, overweight is a condition where a person's body weight is greater than what is considered healthy for their height and body composition. The term "overweight" is often used interchangeably with "obesity," but they are not the same thing. The body mass index (BMI) is a commonly used tool to determine whether a person is overweight or obese. BMI is calculated by dividing a person's weight in kilograms by their height in meters squared. A BMI of 25 to 29.9 is considered overweight, while a BMI of 30 or higher is considered obese. Being overweight can increase the risk of developing a variety of health problems, including heart disease, stroke, type 2 diabetes, certain types of cancer, and osteoarthritis. Therefore, it is important to maintain a healthy weight through a balanced diet and regular physical activity.

Cognition disorders refer to a group of conditions that affect an individual's ability to think, reason, remember, and learn. These disorders can be caused by a variety of factors, including brain injury, neurological disorders, genetic factors, and aging. Cognition disorders can manifest in different ways, depending on the specific area of the brain that is affected. For example, a person with a memory disorder may have difficulty remembering important information, while someone with a language disorder may have trouble expressing themselves or understanding what others are saying. Some common types of cognition disorders include: 1. Alzheimer's disease: A progressive neurological disorder that affects memory, thinking, and behavior. 2. Dementia: A general term used to describe a decline in cognitive function that is severe enough to interfere with daily life. 3. Delirium: A sudden onset of confusion and disorientation that can be caused by a variety of factors, including illness, medication side effects, or dehydration. 4. Aphasia: A language disorder that affects a person's ability to speak, understand, or use language. 5. Attention deficit hyperactivity disorder (ADHD): A neurodevelopmental disorder that affects a person's ability to focus, pay attention, and control impulses. 6. Learning disorders: A group of conditions that affect a person's ability to acquire and use knowledge and skills. Cognition disorders can have a significant impact on a person's quality of life, and treatment options may include medication, therapy, and lifestyle changes. Early diagnosis and intervention are important for managing these conditions and improving outcomes.

In the medical field, particulate matter (PM) refers to tiny solid or liquid particles that are suspended in the air. These particles can be inhaled into the lungs and can cause a range of health problems, including respiratory and cardiovascular diseases. PM can be classified based on their size, with smaller particles being more harmful to health. PM2.5 refers to particles with a diameter of 2.5 micrometers or less, while PM10 refers to particles with a diameter of 10 micrometers or less. These particles can penetrate deep into the lungs and even enter the bloodstream, causing inflammation and oxidative stress. Exposure to high levels of PM can increase the risk of developing conditions such as asthma, chronic obstructive pulmonary disease (COPD), lung cancer, and heart disease. It can also exacerbate existing health conditions and increase the risk of premature death. In summary, particulate matter is a type of air pollution that can have serious health consequences when inhaled. It is an important consideration in public health and environmental policy, and efforts are being made to reduce its levels in the air.

Prenatal Exposure Delayed Effects (PEDs) refer to the long-term health effects that can occur in an individual as a result of exposure to environmental or genetic factors during pregnancy. PEDs can manifest in a variety of ways, including physical, behavioral, and cognitive impairments, and can occur even if the exposure occurred many years before the individual's birth. PEDs can result from exposure to a wide range of substances, including drugs, alcohol, tobacco, pollutants, and infections. These exposures can affect the developing fetus in various ways, including disrupting normal growth and development, altering gene expression, and causing damage to organs and systems. PEDs can also result from genetic factors, such as inherited disorders or mutations. These genetic factors can increase the risk of developing certain health conditions, such as autism, ADHD, and learning disabilities, even if the individual was not exposed to any environmental factors during pregnancy. Overall, PEDs highlight the importance of taking steps to protect pregnant women and their developing fetuses from exposure to harmful substances and environmental factors, as well as the need for ongoing monitoring and support for individuals who may be at risk for PEDs.

In the medical field, oxygen is a gas that is essential for the survival of most living organisms. It is used to treat a variety of medical conditions, including respiratory disorders, heart disease, and anemia. Oxygen is typically administered through a mask, nasal cannula, or oxygen tank, and is used to increase the amount of oxygen in the bloodstream. This can help to improve oxygenation of the body's tissues and organs, which is important for maintaining normal bodily functions. In medical settings, oxygen is often used to treat patients who are experiencing difficulty breathing due to conditions such as pneumonia, chronic obstructive pulmonary disease (COPD), or asthma. It may also be used to treat patients who have suffered from a heart attack or stroke, as well as those who are recovering from surgery or other medical procedures. Overall, oxygen is a critical component of modern medical treatment, and is used in a wide range of clinical settings to help patients recover from illness and maintain their health.

Genetic predisposition to disease refers to the tendency of an individual to develop a particular disease or condition due to their genetic makeup. It means that certain genes or combinations of genes increase the risk of developing a particular disease or condition. Genetic predisposition to disease is not the same as having the disease itself. It simply means that an individual has a higher likelihood of developing the disease compared to someone without the same genetic predisposition. Genetic predisposition to disease can be inherited from parents or can occur due to spontaneous mutations in genes. Some examples of genetic predisposition to disease include hereditary breast and ovarian cancer, Huntington's disease, cystic fibrosis, and sickle cell anemia. Understanding genetic predisposition to disease is important in medical practice because it can help identify individuals who are at high risk of developing a particular disease and allow for early intervention and prevention strategies to be implemented.

Cardiovascular diseases (CVDs) are a group of conditions that affect the heart and blood vessels. They are the leading cause of death worldwide, accounting for more than 17 million deaths each year. CVDs include conditions such as coronary artery disease (CAD), heart failure, arrhythmias, valvular heart disease, peripheral artery disease (PAD), and stroke. These conditions can be caused by a variety of factors, including high blood pressure, high cholesterol, smoking, diabetes, obesity, and a family history of CVDs. Treatment for CVDs may include lifestyle changes, medications, and in some cases, surgery.

HIV (Human Immunodeficiency Virus) infections refer to the presence of the HIV virus in the body. HIV is a retrovirus that attacks and weakens the immune system, making individuals more susceptible to infections and diseases. HIV is transmitted through contact with infected bodily fluids, such as blood, semen, vaginal fluids, and breast milk. The most common modes of transmission include unprotected sexual contact, sharing needles or syringes, and from mother to child during pregnancy, childbirth, or breastfeeding. HIV infections can be diagnosed through blood tests that detect the presence of the virus or antibodies produced in response to the virus. Once diagnosed, HIV can be managed with antiretroviral therapy (ART), which helps to suppress the virus and prevent the progression of the disease to AIDS (Acquired Immune Deficiency Syndrome). It is important to note that HIV is not the same as AIDS. HIV is the virus that causes AIDS, but not everyone with HIV will develop AIDS. With proper treatment and management, individuals with HIV can live long and healthy lives.

In the medical field, arsenic is a toxic heavy metal that can cause a range of health problems when ingested, inhaled, or absorbed through the skin. Arsenic is found naturally in the environment and can also be released into the air, water, and soil through human activities such as mining, smelting, and the use of certain pesticides and herbicides. Long-term exposure to arsenic can lead to a variety of health problems, including skin lesions, respiratory problems, cardiovascular disease, and cancer. Arsenic poisoning can cause symptoms such as nausea, vomiting, abdominal pain, diarrhea, and headache. In severe cases, it can lead to organ failure and death. In the medical field, arsenic poisoning is treated by removing the source of exposure and providing supportive care to manage symptoms. In some cases, chelation therapy may be used to remove arsenic from the body. It is important to note that the risk of arsenic poisoning can be reduced by avoiding exposure to contaminated water and soil, and by following safe practices when handling and disposing of arsenic-containing materials.

Schizophrenia is a severe mental disorder characterized by a range of symptoms that affect a person's thoughts, emotions, and behavior. These symptoms can include hallucinations (hearing or seeing things that are not there), delusions (false beliefs that are not based in reality), disorganized thinking and speech, and problems with emotional expression and social interaction. Schizophrenia is a chronic condition that can last for a lifetime, although the severity of symptoms can vary over time. It is not caused by a single factor, but rather by a complex interplay of genetic, environmental, and neurobiological factors. Treatment for schizophrenia typically involves a combination of medication, therapy, and support from family and friends. While there is no cure for schizophrenia, with proper treatment, many people are able to manage their symptoms and lead fulfilling lives.

In the medical field, weight gain refers to an increase in body weight over a period of time. It can be caused by a variety of factors, including changes in diet, lack of physical activity, hormonal imbalances, certain medications, and medical conditions such as hypothyroidism or polycystic ovary syndrome (PCOS). Weight gain can be measured in kilograms or pounds and is typically expressed as a percentage of body weight. A healthy weight gain is generally considered to be 0.5 to 1 kilogram (1 to 2 pounds) per week, while an excessive weight gain may be defined as more than 0.5 to 1 kilogram (1 to 2 pounds) per week over a period of several weeks or months. In some cases, weight gain may be a sign of a more serious medical condition, such as diabetes or heart disease. Therefore, it is important to monitor weight changes and consult with a healthcare provider if weight gain is a concern.

Disease progression refers to the worsening or progression of a disease over time. It is a natural course of events that occurs in many chronic illnesses, such as cancer, heart disease, and diabetes. Disease progression can be measured in various ways, such as changes in symptoms, physical examination findings, laboratory test results, or imaging studies. In some cases, disease progression can be slowed or stopped through medical treatment, such as medications, surgery, or radiation therapy. However, in other cases, disease progression may be inevitable, and the focus of treatment may shift from trying to cure the disease to managing symptoms and improving quality of life. Understanding disease progression is important for healthcare providers to develop effective treatment plans and to communicate with patients about their condition and prognosis. It can also help patients and their families make informed decisions about their care and treatment options.

General linear model Generalized linear model Linear predictor function Linear system Linear regression Statistical model ... An example of a linear time series model is an autoregressive moving average model. Here the model for values { X t {\ ... Note that here the "linear" part of the term "linear model" is not referring to the coefficients Ï• i {\displaystyle \phi _{i}} ... "linear model" refers to the structure of the above relationship in representing X t {\displaystyle X_{t}} as a linear function ...
Log-linear analysis General linear model Generalized linear model Boltzmann distribution Elasticity Gujarati, Damodar N.; ... A log-linear model is a mathematical model that takes the form of a function whose logarithm equals a linear combination of the ... Poisson regression for contingency tables, a type of generalized linear model. The specific applications of log-linear models ... while c and the wi stand for the model parameters. The term may specifically be used for: A log-linear plot or graph, which is ...
For the "linear probability model", this relationship is a particularly simple one, and allows the model to be fitted by linear ... Aldrich, John H.; Nelson, Forrest D. (1984). "The Linear Probability Model". Linear Probability, Logit, and Probit Models. Sage ... In statistics, a linear probability model (LPM) is a special case of a binary regression model. Here the dependent variable for ... models such as the logit model or the probit model are more commonly used. More formally, the LPM can arise from a latent- ...
The general linear model and the generalized linear model (GLM) are two commonly used families of statistical methods to relate ... In that sense it is not a separate statistical linear model. The various multiple linear regression models may be compactly ... ISBN 0-12-471252-5. McCullagh, P.; Nelder, J. A. (1989), "An outline of generalized linear models", Generalized Linear Models, ... generalized linear models may be used to relax assumptions about Y and U. The general linear model incorporates a number of ...
... very important example of a generalized linear model (also an example of a general linear model) is linear regression. In ... Such a model is a log-odds or logistic model. Generalized linear models cover all these situations by allowing for response ... The general linear model may be viewed as a special case of the generalized linear model with identity link and responses ... As most exact results of interest are obtained only for the general linear model, the general linear model has undergone a ...
In statistics, a proper linear model is a linear regression model in which the weights given to the predictor variables are ... Unit-weighted regression is the most common example of an improper linear model. Dawes, R. M. (1979). "The robust beauty of ... Simple regression analysis is the most common example of a proper linear model. ... improper linear models in decision making". American Psychologist. 34 (7): 571-582. doi:10.1037/0003-066X.34.7.571. S2CID ...
used partially linear model to analysis collected data in 2000. So far, partially linear model was optimized in many other ... Zeger and Diggle applied partially linear model for their work. Partially linear model primarily contributes to the estimation ... The partially linear model enables and simplifies the linear transformation of data (Engle, Granger, Rice and Weiss, 1986). ... A partially linear model is a form of semiparametric model, since it contains parametric and nonparametric elements. ...
The generalized functional linear model (GFLM) is an extension of the generalized linear model (GLM) that allows one to regress ... James (2002). "Generalized linear models with functional predictors". Journal of the Royal Statistical Society, Series B. 64 (3 ... Articles with short description, Short description matches Wikidata, Generalized linear models). ... the GFLM Functional additive models Functional data analysis Functional principal component analysis Generalized linear model ...
The linear no-threshold model (LNT) is a dose-response model used in radiation protection to estimate stochastic health effects ... The validity of the LNT model, however, is disputed, and other significant models exist: the threshold model, which assumes ... the supra-linear model is verified. It has been argued that the LNT model may have created an irrational fear of radiation. ... The LNT model assumes there is no lower threshold at which stochastic effects start, and assumes a linear relationship between ...
For example, in discrete choice models, one has conditional logit models, nested logit models, generalized logit models, and ... In statistics, the class of vector generalized linear models (VGLMs) was proposed to enlarge the scope of models catered for by ... and include 3 of the most important statistical regression models: the linear model, Poisson regression for counts, and ... therefore this model is also called the cumulative probit model. In general they are called cumulative link models. For ...
Generalized Linear Mixed Models, CRC Press Jiang, J. (2007), Linear and Generalized Linear Mixed Models and Their Applications ... a generalized linear mixed model (GLMM) is an extension to the generalized linear model (GLM) in which the linear predictor ... Generalized linear mixed models are a special cases of hierarchical generalized linear models in which the random effects are ... They also inherit from GLMs the idea of extending linear mixed models to non-normal data. GLMMs provide a broad range of models ...
Sigma model Chiral model Little Higgs Skyrmion, a soliton in non-linear sigma models Polyakov action WZW model Fubini-Study ... This article deals primarily with the quantization of the non-linear sigma model; please refer to the base article on the sigma ... The non-linear Ïƒ-model was introduced by Gell-Mann & LÃ©vy (1960, section 6), who named it after a field corresponding to a ... a metric often used with non-linear sigma models Ricci flow Scale invariance Gell-Mann, M.; LÃ©vy, M. (1960), "The axial vector ...
Such models provide a structure and a computational procedure for fitting generalized linear models or GLMs whose model matrix ... It based on the generalized linear model with the design matrix written as a Kronecker product. The generalized linear array ... Currie, I. D.; Durban, M.; Eilers, P. H. C. (2006). "Generalized linear array models with applications to multidimensional ... In statistics, the generalized linear array model (GLAM) is used for analyzing data sets with array structures. ...
A history of the linear model of innovation may be found in BenoÃ®t Godin's The Linear Model of Innovation: The Historical ... Two versions of the linear model of innovation are often presented: "technology push" model "market pull" model From the 1950s ... Sales The linear models of innovation supported numerous criticisms concerning the linearity of the models. These models ignore ... The Linear Model of Innovation was an early model designed to understand the relationship of science and technology that begins ...
The linear transform model is a common and widespread assumption used in the interpretation of fMRI studies. However, some ... The linear transform model refers to a fundamental assumption guiding the analysis of functional Magnetic Resonance Imaging ( ... Specifically, the model holds that the fMRI signal is approximately proportional to a measure of local neural activity, ...
The fluid model equivalent to the standard linear solid model includes a dashpot in series with the Kelvin-Voigt model and is ... The standard linear solid (SLS), also known as the Zener model, is a method of modeling the behavior of a viscoelastic material ... Often, the simpler Maxwell model and the Kelvin-Voigt model are used. These models often prove insufficient, however; the ... The standard linear solid model combines aspects of the Maxwell and Kelvin-Voigt models to accurately describe the overall ...
... the mixed linear model is the normal conjugate hierarchical generalized linear models. A summary of commonly used models are: ... Moreover, the generalized linear mixed model (GLMM) is a special case of the hierarchical generalized linear model. In ... There are different techniques to fit a hierarchical generalized linear model. Hierarchical generalized linear model have been ... In statistics, hierarchical generalized linear models extend generalized linear models by relaxing the assumption that error ...
The linear-nonlinear-Poisson (LNP) cascade model is a simplified functional model of neural spike responses. It has been ... There are three stages of the LNP cascade model. The first stage consists of a linear filter, or linear receptive field, which ... If the nonlinearity f {\displaystyle f} is a fixed invertible function, then the LNP model is a generalized linear model. In ... the linear stage of the LNP model can be generalized to a bank of linear filters, and the nonlinearity becomes a function of ...
A specialized form of pharmacokinetics modeling, physiology-based pharmacokinetic (PBPK) modeling can in some cases also be ... Nonlinear mixed-effects models are a special case of regression analysis for which a range of different software solutions are ... Nonlinear mixed effects models are therefore estimated according to Maximum Likelihood principles. Specific estimation methods ... SPSS at the moment does not support non-linear mixed effects methods. WinBUGS is an implementation of the Metropolis-Hastings ...
Ursin and Toverud compared different Q models including the above model (SLS-model). In order to compare the different models ... A standard linear solid Q model (SLS) for attenuation and dispersion is one of many mathematical Q models that gives a ... This model was compared with the Kolsky-Futterman model. The Kolsky-Futterman model was first described in the article ' ... The standard linear solid model is developed from the stress-strain relation. Using a linear combination of springs and ...
Other possible models are the conditional equiprobability model and the mutual dependence model. Each log-linear model can be ... Log-linear analysis models can be hierarchical or nonhierarchical. Hierarchical models are the most common. These models ... The saturated model is the model that includes all the model components. This model will always explain the data the best, but ... The log-linear models can be thought of to be on a continuum with the two extremes being the simplest model and the saturated ...
"General linear models" are also called "multivariate linear models". These are not the same as multivariable linear models ( ... Errors-in-variables models (or "measurement error models") extend the traditional linear regression model to allow the ... In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are ... and a special case of general linear models, restricted to one dependent variable. The basic model for multiple linear ...
In statistics, linear least squares problems correspond to a particularly important type of statistical model called linear ... The approach is called linear least squares since the assumed function is linear in the parameters to be estimated. Linear ... this model is still linear in the unknown parameters (now just Î² 1 {\displaystyle \beta _{1}} ), so linear least squares still ... More generally, one can have n {\displaystyle n} regressors x j {\displaystyle x_{j}} , and a linear model y = Î² 0 + âˆ‘ j = 1 n ...
The natural generalization of a linear utility function to that model is an additive set function. This is the common case in ... Define a linear economy as an exchange economy in which all agents have linear utility functions. A linear economy has several ... Eaves, B.Curtis (1976). "A finite algorithm for the linear exchange model" (PDF). Journal of Mathematical Economics. 3 (2): 197 ... Gale, David (1976). "The linear exchange model". Journal of Mathematical Economics. 3 (2): 205-209. doi:10.1016/0304-4068(76) ...
The model evidence of the Bayesian linear regression model presented in this section can be used to compare competing linear ... Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear ... ISBN 0-340-52922-9. Bayesian estimation of linear models (R programming wikibook). Bayesian linear regression as implemented in ... The simplest and most widely used version of this model is the normal linear model, in which y {\displaystyle y} given X {\ ...
... and linear models which "do not try to reconstitute the whole melody in order of real time succession of melodic events. Linear ... According to Nattiez, Boretz "seems to be confusing his own formal, logical model with an immanent essence he then ascribes to ... Is it not a most impressive moment?". Formalized analyses propose models for melodic functions or simulate music. Meyer ... These are in contrast to the formalized models of Milton Babbitt and Boretz. ...
In other words, if linear regression is the appropriate model for a set of data points whose sample correlation coefficient is ... Edward J. Dudewicz & Satya N. Mishra (1988). "Section 14.1: Estimation of regression parameters; Linear models". Modern ... such a line that minimizes the sum of squared residuals of the linear regression model. In other words, numbers Î± and Î² solve ... He quantified this trend, and in doing so invented linear regression analysis, thus laying the groundwork for much of modern ...
He was a leader in the field of linear and mixed models in statistics, and published widely on the topics of linear models, ... Searle, S. R. (1997). "The matrix Handling of BLUE and BLUP in the mixed linear model". Linear Algebra and Its Applications. ... Searle, S. R. (1994). "Extending some results and proofs for the singular linear model". Linear Algebra and Its Applications. ... The statistics of linear models: back to basics'". Statistics and Computing. 5 (2): 103-107. doi:10.1007/BF00143939. S2CID ...
Linear model Linear regression Makhoul, J. (1975). "Linear prediction: A tutorial review". Proceedings of the IEEE. 63 (4): 561 ... In statistics and in machine learning, a linear predictor function is a linear function (linear combination) of a set of ... In some models (standard linear regression, in particular), the equations for each of the data points i = 1, ..., n are stacked ... All sorts of non-linear functions of the explanatory variables can be fit by the model. There is no particular need for the ...
She has written books on the design of experiments, on association schemes, and on linear models in statistics. Bailey's first ... Bailey, R. A. (1994). Normal linear models. London: External Advisory Service, University of London. ISBN 0-7187-1176-9. Bailey ... ISBN 978-0-521-68357-9. Speed, T. P.; Bailey, R. A. (1987). "Factorial Dispersion Models". International Statistical Review / ...
... This view is a snapshot, at-a-glance summary of the model and its fit. ... Covariance Parameters (generalized linear mixed models). *Estimated Means: Significant Effects (generalized linear mixed models ... Smaller values indicate better models. The BIC also "penalizes" overparameterized models (complex models with a large number of ... Smaller values indicate better models. The AICC "corrects" the AIC for small sample sizes. As the sample size increases, the ...
For a predictive model, this corresponds to a model that predicts more precisely. In our individual model for OD, RSquare is ... Fitting the Multiple Linear Regression Model. Recall that the method of least squares is used to find the best-fitting line for ... Here, we fit a multiple linear regression model for Removal, with both OD and ID as predictors. Notice that the coefficients ... The coefficient for OD (0.559) is pretty close to what we see in the simple linear regression model, but its slightly higher. ...
Linear Models (lm, ANOVA and ANCOVA) in Agriculture Linear Mixed-Effects Models This class of models are used to account for ... For the dataset please look at the previous post.Just to explain the syntax to use linear mixed-effects model in R for cluster ... At the beginning on this tutorial we explored the equation that supports linear model: This equation can be seen as split into ... Once again we can use the function summary to explore our results: , summary(lme1) Linear mixed-effects model fit by REML Data ...
Modeling with Linear Equations - 1.3 Exercises - Page 99 70 including work step by step written by community members like you. ... Modeling with Linear Equations - 1.3 Exercises - Page 99: 71a Previous Answer Chapter 1 - 1.3 - Modeling with Linear Equations ... Chapter 1 - 1.3 - Modeling with Linear Equations - 1.3 Exercises - Page 99: 70. Answer. 48.001 ... Chapter 1 - 1.3 - Modeling with Linear Equations - 1.3 Exercises - Page 99. 70 ...
A non-linear numerical wave model to investigate the dynamic behaviour of a large diameter monopile-based offshore wind turbine ... Title: A non-linear numerical wave model to investigate the dynamic behaviour of a large diameter monopile-based offshore wind ... A non-linear numerical wave model to investigate the dynamic behaviour of a large diameter monopile-based offshore wind turbine ... The focus of the research, therefore, will be to develop a non-linear numerical wave model to assess the dynamic behaviour of a ...
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Built by CADENAS, the configurator enables customers to instantly find, configure and download a digital 3D CAD model of the ... Helix Linear Technologies launched an online product catalog of 3D CAD models for their popular configurable products, ... 3D CAD models from Helix Linear Technologies go online with interactive product catalog built by CADENAS. 11.07.2018. ... Helix Linear Technologies launched an online product catalog of 3D CAD models for their popular configurable products, ...
Title: Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. Authors: Zhihai Wang, Xijun ... Specifically, HEM consists of a two-level model: (1) a higher-level model to learn the number of cuts that should be selected ... Abstract: Cutting planes (cuts) are important for solving mixed-integer linear programs (MILPs), which formulate a wide range ... To address this challenge, we propose a novel hierarchical sequence model (HEM) to learn cut selection policies via ...
The main challenge was adapting the existing models whose primary focus was containing a hazardous material release t... ... Linear no-threshold model. The linear no-threshold model (LNT), which is used by most regulatory agencies, assumes a direct and ... Whether the actual effect is linear or otherwise remains unknown, and the core principle of radiation safety is to ensure that ... 1] The main challenge was adapting the existing models, whose primary focus was containing a hazardous material release, to one ...
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Panel Data Model Estimation * Linear Factor Models for Asset Pricing * System Regression Models ... linearmodels.. iv.. absorbing.. Interaction * Clinearmodels.. iv.. absorbing.. Interaction Clinearmodels.. iv.. absorbing. ... linearmodels.. iv.. absorbing.. Interaction linearmodels.. iv.. absorbing.. Interaction Contents * Clinearmodels.. iv. ... linearmodels.iv.absorbing.InteractionÂ¶. class linearmodels.iv.absorbing.Interaction(cat: ndarray , DataArray , DataFrame , ...
Linear mixed-effect models. We used linear mixed-effect models to test the effects of the experimental treatment on restoration ... Extended Data Table 1 ANOVA of the linear mixed-effect models for biodiversity and ecosystem functioning. Full size table. ... model selection influenced only the inclusion of structural complexity and tree dominance in the linear model (1). Effects of ... as this improved the model diagnostics before applying the respective linear mixed-effect models; whereas we used logarithmic ...
Topics covered include a review of multiple linear regression and the analysis of variance, log-linear models for contingency ... Additional topics may include Bayesian analysis for generalized linear models and generalized mixed effect models. ... Generalised Linear Models A graduate course offered by the Rsch Sch of Finance, Actuarial Studies & App Stats. ... Course Description: This course is intended to introduce students to generalised linear modelling methods, with emphasis on, ...
Coefficient of determination R2 and intra-class correlation coefficient ICC from generalized linear mixed-effects models ... Coefficient of determination R2 and intra-class correlation coefficient ICC from generalized linear mixed-effects models ... Coefficient of determination R2 and intra-class correlation coefficient ICC from generalized linear mixed-effects models ... Coefficient of determination R2 and intra-class correlation coefficient ICC from generalized linear mixed-effects models ...
The linear regression model is employed to analyze this correlation and extract texture features that characterize the samples ... In this paper, we propose a texture analysis and classification approach kith the linear regression model based on the wavelet ... The linear regression model is employed to analyze this correlation and extract texture features that characterize the samples ... Texture Analysis and Classification With Linear Regression Model Based on Wavelet Transform. IEEE Transactions on Image ...
... Rev. Latinoam. Psicol. [online]. 2008, vol.40, n.1, ... This paper presents an illustration of the integration of cognitive psychology and psychometric models to determine sources of ... and the goodness of fit of items to both the Rasch and the LLTM models was studied. Results obtained were used to illustrate ...
... simple linear regression is the least squares estimator of a linear regression model with a single explanatory variable.... ... In statistics, simple linear regression is the least squares estimator of a linear regression model with a single explanatory ... In other words, simple linear regression fits a straight line through the set of n points in such a way that makes the sum of ... Kenney, J. F. and Keeping, E. S. (1962) "Linear Regression and Correlation." Ch. 15 in Mathematics of Statistics, Pt. 1, 3rd ed ...
Procedures for refining model parameters after estimating a model or constructing the model with initial parameter guesses. ... Refine Linear Parametric Models. When to Refine Models. There are two situations where you can refine estimates of linear ... Initial model. drop-down list or type the model name.. The model name must be in the Model Board of the System Identification ... models, tfest. for idtf. models, and greyest. for idgrey. models.. The general syntax for refining initial models is as follows ...
Build a model in Excel and paste a screenshot here. Use "FORMULATEXT" in your model to show calculations. ... Build a model in Excel and paste a screenshot here. Use "FORMULATEXT" in your model to show calculations. ... Revise your model so that SolverTable can be used to investigate these changes when the percentage increase varies from 2% to ... Provide the complete linear programing formulation. Clearly specify decision variables, objective function and constraints. ...
Linear Filtering for Asymmetric Stochastic Volatility Models Number of pages: 9 Posted: 01 Apr 2005 ... Regime-Switching Factor Models in Which the Number of Factors Defines the Regime Number of pages: 9 Posted: 01 Dec 2010 Last ... Regime-Switching Factor Models in Which the Number of Factors Defines the Regime Economics Letters, Forthcoming ... Multivariate Stochastic Volatility Models with Correlated Errors Number of pages: 31 Posted: 21 Jan 2006 ...
sklearn.linear_model. .PassiveAggressiveClassifierÂ¶. class sklearn.linear_model.. PassiveAggressiveClassifier. (C=1.0, fit_ ... from sklearn.linear_model import PassiveAggressiveClassifier ,,, from sklearn.datasets import make_classification ,,, ,,, X, y ... Fit linear model with Passive Aggressive algorithm.. Parameters:. X : {array-like, sparse matrix}, shape = [n_samples, n_ ... Fit linear model with Passive Aggressive algorithm.. Parameters:. X : {array-like, sparse matrix}, shape = [n_samples, n_ ...
Spatial regression models: ordinary least squares; generalized linear mixed models; geographically weighted regression Bayesian ... Regression models can be applied to spatial data to determine what independent variables might explain a spatially dependent ... Network analysis, time-series animations, map series, linked micromaps, and spatiotemporal modeling are methods for evaluating ... Mean/median center Directional distribution; standard deviational ellipse; linear directional mean. Identify a geographic ...
A Double Bootstrap Method for Analyzing Linear Models with Autoregressive Errors Documentation for package DBfit version 2.0 ... A Double Bootstrap Method for Analyzing Linear Models With Autoregressive Errors. dbfit. The main function for the double ... A Double Bootstrap Method for Analyzing Linear Models With Autoregressive Errors. boot1. First Boostrap Procedure For parameter ...
Model upgrading to augment linear model capabilities into nonlinear regions. / Cooper, S. B.; Delli Carri, A.; Di Maio, D. ... Cooper SB, Delli Carri A, Di Maio D. Model upgrading to augment linear model capabilities into nonlinear regions. In Nonlinear ... Cooper, S. B. ; Delli Carri, A. ; Di Maio, D. / Model upgrading to augment linear model capabilities into nonlinear regions. ... Cooper, SB, Delli Carri, A & Di Maio, D 2016, Model upgrading to augment linear model capabilities into nonlinear regions. in ...
We fitted a Poisson generalized linear model (12) for the outcome variable influenza (H9N2) subtype weekly isolation counts ... Adjusted RR, associated 95% CI, and p values of Poisson generalized linear models for influenza (H9N2) virus isolation rates by ... To verify model goodness-of-fit, 2 coauthors independently viewed residual plots and verified that the model fit was adequate. ... We only retained statistically significant interaction terms in the final model.. We fitted separate models for chickens and ...
STAT-456 Generalized Linear Models and Dependent Data Analysis. Brittney E. Bailey (Section 01) ...
Bootstrap confidence intervals on a linear-plateau model in R. Crop yields go up a line, then level off at some uncertain point ... Then create the bootstraps, and fit the LP model to each. But what if a model fails? The purrr. package includes possibly(). ... but well fit a nonlinear model known as the linear-plateau (LP), or lin-plat1. Looking at the plot, notice how the relative ... set.seed(911) cotton %,% bootstraps(times = 2000) %,% mutate(models = map(splits, possibly(fit_LP, otherwise = NULL)), coefs = ...
• Linear regression analyses were used to develop prediction equations, the amount of predictability, and significance for static and dynamic peak back-compressive forces based on a static origin and destination average (SODA) back-compressive force. (cdc.gov)
• A linear regression model adjusted for potential confounders suggested that increased ELCE was associated with less annual cognitive decline compared with lower levels of ELCE. (medscape.com)
• Linear regression models showed that every one-unit increase in ELCE score was associated with a lower global AD pathology score (estimate, âˆ’0.057) and lower levels of tau (estimate, âˆ’0.188) and beta amyloid (estimate, âˆ’0.136). (medscape.com)
• To cap the deadly effect caused by the pandemic, we apply a statistical modelling approach to investigate and predict COVID-19 incidence. (who.int)
• Statistical forecast models play a role in predicting future epidemic threats, managing of societal, economic, cultural, and public health matters. (who.int)
• Fig. 2 be used for generating models for statistical analysis, and output can be generated in the form of reports and graphs. (who.int)
• This paper presents an illustration of the integration of cognitive psychology and psychometric models to determine sources of item difficulty in an Arithmetic Test (AT), constructed by the authors, by means of its analysis with the LLTM. (bvsalud.org)
• Several approaches were attempted for harmonizing the 2003-2006 25(OH)D. A model based on RIA quality control pool data was selected because the results should be independent of any empirical trend in the sample participant data. (cdc.gov)
• Results: As workforce mobility increases, relative bias in treatment effects derived from standard models to analyze cluster-randomized trials also increases. (cdc.gov)
• In order to reach this aim, a group of operations required to solve the items of the test were proposed, the dimensionality was evaluated, and the goodness of fit of items to both the Rasch and the LLTM models was studied. (bvsalud.org)
• The ARIMA (11,1,11) model for the complete data set was finally selected among ARIMA models based upon the parameter test and the Box-Ljung test. (who.int)
• Europe use a variety of classifications to rec- publication, collaborative effort and shared ord cancer incidence, so the data in EUROCIM authorship of publications are strongly en- have been converted to ensure consistency. (who.int)
• in the AFNI suite is a program that runs FMRI group analysis with a linear mixed-effects modeling approach. (nih.gov)
• The Group Analysis slides and its Hands-On presentation from AFNI workshop are also good resources for various modeling approaches. (nih.gov)
• In this way the approach provides a unified framework for a range of models that have previously been used in this setting, and new more flexible variants. (nih.gov)
• This report presents a comprehensive approach to statistical modeling of post-earthquake ignitions and to data compilation for such modeling, and applies it to present day California. (buffalo.edu)
• The new approach recognizes the discrete nature of ignition counts by using generalized linear and generalized linear mixed models for the first time in this type of application. (buffalo.edu)
• In contrast, we present a unified approach that directly incorporates geometric structure into the estimation process by exploiting the joint eigenproperties of the predictors and a linear penalty operator. (nih.gov)
• Linear Mixed-Effects Modeling Approach to FMRI Group Analysis. (nih.gov)
• NTP is convening an expert panel on October 23-25, 2017, at the National Institute of Environmental Health Sciences, Research Triangle Park, NC to obtain input on specific details of its proposed approach to genomic dose-response modeling. (nih.gov)
• NTP's proposed approach is in large part consistent with an approach to genomic dose-response modeling outlined by Thomas et al. (nih.gov)
• Two additional issues, which are not immediately central to the data modeling pipeline but are critical to overall success of the genomic dose-response approach, are study design and biological interpretation of findings. (nih.gov)
• NTP will also continue to monitor the scientific literature with regard to the development of improved approaches to data modeling and analysis. (nih.gov)
• To account for this behavior, we developed an equilibrium self-association model that describes the final size distributions of apoC-II fibrils formed at different starting concentrations. (nih.gov)
• Environmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure-response relationship. (nih.gov)
• This family of models is implemented in the package dlnm within the statistical environment R. To illustrate the methodology we use examples of DLNMs to represent the relationship between temperature and mortality, using data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) for New York during the period 1987-2000. (nih.gov)
• Advances in statistical methods and free point and click software have made it easy to select a sample size for clustered and longitudinal designs with linear mixed models. (nih.gov)
• 15] in which biological samples are distributed over a broad dose range, which allows for more accurate estimates of model parameters. (nih.gov)
• He is the first author of two books on linear model theory and practice. (nih.gov)
• It includes careful model selection and goodness-of-fit analyses, examines multiple covariates to estimate ignitions, and uses a census tract as a unit of study to enable better estimates at a finer geographic resolution. (buffalo.edu)
• This structure is inherent in the output from an increasing number of biomedical technologies, and a functional linear model is often used to estimate the relationship between the predictor functions and scalar responses. (nih.gov)
• Our fluorescence quenching and sedimentation velocity experiments with Alexa488-labeled apoC-II indicated a time-dependent subunit interchange for both linear and closed-loop fibrils, while dilution experiments using mature fibrils indicated a shift to smaller size distributions consistent with a reversible assembly pathway. (nih.gov)
• Model I. Const Capillary Transit Time (TT) and Varying Large Vessel TT. (nih.gov)
• [ 1 ] The main challenge was adapting the existing models, whose primary focus was containing a hazardous material release, to one that reflected the chaos of a large-scale disaster involving a large number of affected individuals. (medscape.com)
• Here we develop the family of distributed lag non-linear models (DLNM), a modelling framework that can simultaneously represent non-linear exposure-response dependencies and delayed effects. (nih.gov)
• This paper presents an illustration of the integration of cognitive psychology and psychometric models to determine sources of item difficulty in an Arithmetic Test (AT), constructed by the authors, by means of its analysis with the LLTM. (bvsalud.org)
• Or is that model supposed to span all 8 runs? (nih.gov)
• Sure, modeling that in just the last 4 runs makes sense. (nih.gov)
• I had initially gathered that all runs were in a single model. (nih.gov)