**Linear Models**: 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.

**Models, Statistical**: 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.

**Nonlinear Dynamics**: 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.

**Algorithms**: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.

**Computer Simulation**: Computer-based representation of physical systems and phenomena such as chemical processes.

**Data Interpretation, Statistical**: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.

**Bayes Theorem**: 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.

**Breeding**: The production of offspring by selective mating or HYBRIDIZATION, GENETIC in animals or plants.

**Models, Genetic**: 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.

**Biostatistics**: The application of STATISTICS to biological systems and organisms involving the retrieval or collection, analysis, reduction, and interpretation of qualitative and quantitative data.

**Longitudinal Studies**: Studies in which variables relating to an individual or group of individuals are assessed over a period of time.

**Regression Analysis**: 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.

**Models, Biological**: 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.

**Likelihood Functions**: 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.

**Least-Squares Analysis**: 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.

**Models, Neurological**: 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.

**Quantitative Trait Loci**: Genetic loci associated with a QUANTITATIVE TRAIT.

**Reproducibility of Results**: 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.

**Time Factors**: Elements of limited time intervals, contributing to particular results or situations.

**Poisson Distribution**: 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.

**Quantitative Trait, Heritable**: A characteristic showing quantitative inheritance such as SKIN PIGMENTATION in humans. (From A Dictionary of Genetics, 4th ed)

**Magnetic Resonance Imaging**: 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.

**Normal Distribution**: 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.

**Cross-Sectional Studies**: 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.

**Models, Theoretical**: 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.

**Biometry**: The use of statistical and mathematical methods to analyze biological observations and phenomena.

**Cohort Studies**: 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.

**Risk Factors**: 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 Factors**: 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.

**Multivariate Analysis**: 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.

**Principal Component Analysis**: Mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components.

**Image Processing, Computer-Assisted**: 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.

**Questionnaires**: 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.

**Polymorphism, Single Nucleotide**: A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.

**United States**

**Parasitic Diseases, Animal**: Infections or infestations with parasitic organisms. The infestation may be experimental or veterinary.

**Statistics as Topic**: 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.

**Brain Mapping**: Imaging techniques used to colocalize sites of brain functions or physiological activity with brain structures.

**Monte Carlo Method**: 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)

**Analysis of Variance**: A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable.

**Genotype**: The genetic constitution of the individual, comprising the ALLELES present at each GENETIC LOCUS.

**Brain**: 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.

**Software**: Sequential operating programs and data which instruct the functioning of a digital computer.

**Gene Expression Profiling**: The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.

**Signal-To-Noise Ratio**: The comparison of the quantity of meaningful data to the irrelevant or incorrect data.

**Phenotype**: The outward appearance of the individual. It is the product of interactions between genes, and between the GENOTYPE and the environment.

**Sex Factors**: 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.

**Oligonucleotide Array Sequence Analysis**: 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.

**Body Mass Index**: 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)

**Health Care Costs**: 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.

**Weather**: The state of the ATMOSPHERE over minutes to months.

**Seasons**: 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)

**Genetic Variation**: Genotypic differences observed among individuals in a population.

**Hip Dysplasia, Canine**: A hereditary disease of the hip joints in dogs. Signs of the disease may be evident any time after 4 weeks of age.

**Air Pollution**: 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.

**Neural Networks (Computer)**: 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.

**Logistic Models**: 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.

**Case-Control Studies**: 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.

**Air Pollutants**: 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.

**Retrospective Studies**: 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.

**Prospective Studies**: 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.

**Pregnancy**: The status during which female mammals carry their developing young (EMBRYOS or FETUSES) in utero before birth, beginning from FERTILIZATION to BIRTH.

**Sample Size**: 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)

**Environmental Exposure**: 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.

**Research Design**: 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.

**Cities**: A large or important municipality of a country, usually a major metropolitan center.

**Aging**: The gradual irreversible changes in structure and function of an organism that occur as a result of the passage of time.

**Mathematical Computing**: Computer-assisted interpretation and analysis of various mathematical functions related to a particular problem.

**Markov Chains**: 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.

**Environment**: The external elements and conditions which surround, influence, and affect the life and development of an organism or population.

**Cattle**: 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.

**Image Interpretation, Computer-Assisted**: Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease.

**Severity of Illness Index**: Levels within a diagnostic group which are established by various measurement criteria applied to the seriousness of a patient's disorder.

**Dairying**

**Confidence Intervals**: 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.

**Artifacts**: 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.

**Treatment Outcome**: 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.

**Quality of Life**: 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.

**Follow-Up Studies**: 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.

**Sensitivity and Specificity**: 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)

**Genetic Association Studies**: 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.

**Obesity**: 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).

**Genome-Wide Association Study**: 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.

**Epistasis, Genetic**: 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.

**Computational Biology**: 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.

**Infant, Newborn**: An infant during the first month after birth.

**Mathematics**: The deductive study of shape, quantity, and dependence. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)

**Insurance Claim Review**: 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.

**Climate**: The longterm manifestations of WEATHER. (McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)

**Signal Processing, Computer-Assisted**: Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity.

**Environmental Monitoring**: 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.

**Socioeconomic Factors**: Social and economic factors that characterize the individual or group within the social structure.

**Reference Values**: 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.

**Cluster Analysis**: 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.

**African Americans**: Persons living in the United States having origins in any of the black groups of Africa.

**Body Weight**: The mass or quantity of heaviness of an individual. It is expressed by units of pounds or kilograms.

**European Continental Ancestry Group**: Individuals whose ancestral origins are in the continent of Europe.

**Chromosome Mapping**: Any method used for determining the location of and relative distances between genes on a chromosome.

**Neuropsychological Tests**: 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.

**Georgia**

**Genetic Markers**: A phenotypically recognizable genetic trait which can be used to identify a genetic locus, a linkage group, or a recombination event.

**Spain**: Parliamentary democracy located between France on the northeast and Portugual on the west and bordered by the Atlantic Ocean and the Mediterranean Sea.

**Biological Markers**: 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.

**Birth Weight**: The mass or quantity of heaviness of an individual at BIRTH. It is expressed by units of pounds or kilograms.

**Overweight**: 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".

**Photic Stimulation**: Investigative technique commonly used during ELECTROENCEPHALOGRAPHY in which a series of bright light flashes or visual patterns are used to elicit brain activity.

**Prevalence**: 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.

**Bias (Epidemiology)**: 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.

**Diet**: Regular course of eating and drinking adopted by a person or animal.

**Databases, Factual**: 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.

**Artificial Intelligence**: 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.

**Cognition**: Intellectual or mental process whereby an organism obtains knowledge.

**Visual Fields**: The total area or space visible in a person's peripheral vision with the eye looking straightforward.

**Cognition Disorders**: Disturbances in mental processes related to learning, thinking, reasoning, and judgment.

**Psychomotor Performance**: The coordination of a sensory or ideational (cognitive) process and a motor activity.

**China**: A country spanning from central Asia to the Pacific Ocean.

**Anthropometry**: The technique that deals with the measurement of the size, weight, and proportions of the human or other primate body.

**Linkage Disequilibrium**: 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.

**Motor Activity**: The physical activity of a human or an animal as a behavioral phenomenon.

**Comorbidity**: 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.

**Reaction Time**: The time from the onset of a stimulus until a response is observed.

**Predictive Value of Tests**: 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.

**Siblings**: Persons or animals having at least one parent in common. (American College Dictionary, 3d ed)

**Vegetables**: A food group comprised of EDIBLE PLANTS or their parts.

**Particulate Matter**: 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.

**Prenatal Exposure Delayed Effects**: 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.

**Tomography, Optical Coherence**: 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.

**Ecosystem**: 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)

**Color**: The visually perceived property of objects created by absorption or reflection of specific wavelengths of light.

**Risk Assessment**: 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)

**Visual Field Tests**: Method of measuring and mapping the scope of vision, from central to peripheral of each eye.

**Sex Characteristics**: 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.

**Residence Characteristics**: Elements of residence that characterize a population. They are applicable in determining need for and utilization of health services.

**Statistics, Nonparametric**: 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)

**Pattern Recognition, Automated**: In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed)

**Animal Husbandry**: The science of breeding, feeding and care of domestic animals; includes housing and nutrition.

**Humidity**: A measure of the amount of WATER VAPOR in the air.

**Litter Size**: The number of offspring produced at one birth by a viviparous animal.

**Haplotypes**: 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.

**Smoking**: Inhaling and exhaling the smoke of burning TOBACCO.

**Oxygen**: 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.

**Hospitalization**: The confinement of a patient in a hospital.

**Crosses, Genetic**: 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.

**Population Density**: Number of individuals in a population relative to space.

**Sus scrofa**: A species of SWINE, in the family Suidae, comprising a number of subspecies including the domestic pig Sus scrofa domestica.

**Models, Psychological**: Theoretical representations that simulate psychological processes and/or social processes. These include the use of mathematical equations, computers, and other electronic equipment.

**Depression**: Depressive states usually of moderate intensity in contrast with major depression present in neurotic and psychotic disorders.

**Genetic Linkage**: The co-inheritance of two or more non-allelic GENES due to their being located more or less closely on the same CHROMOSOME.

**Genetic Predisposition to Disease**: A latent susceptibility to disease at the genetic level, which may be activated under certain conditions.

**Cardiovascular Diseases**: Pathological conditions involving the CARDIOVASCULAR SYSTEM including the HEART; the BLOOD VESSELS; or the PERICARDIUM.

**Swine**: 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).

**HIV Infections**: Includes the spectrum of human immunodeficiency virus infections that range from asymptomatic seropositivity, thru AIDS-related complex (ARC), to acquired immunodeficiency syndrome (AIDS).

**Fishes**: A group of cold-blooded, aquatic vertebrates having gills, fins, a cartilaginous or bony endoskeleton, and elongated bodies covered with scales.

**Parity**: The number of offspring a female has borne. It is contrasted with GRAVIDITY, which refers to the number of pregnancies, regardless of outcome.

**Arsenic**: 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)

**Demography**: Statistical interpretation and description of a population with reference to distribution, composition, or structure.

**Exercise**: 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.

**Genetics, Population**: 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.

**Psychometrics**: Assessment of psychological variables by the application of mathematical procedures.

**Outcome Assessment (Health Care)**: 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).

**Health Status**: The level of health of the individual, group, or population as subjectively assessed by the individual or by more objective measures.

**Fourier Analysis**: 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)

**Double-Blind Method**: 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.

**Incidence**: 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.

**Milk**: The white liquid secreted by the mammary glands. It contains proteins, sugar, lipids, vitamins, and minerals.

**Blood Pressure**: PRESSURE of the BLOOD on the ARTERIES and other BLOOD VESSELS.

**Weaning**: Permanent deprivation of breast milk and commencement of nourishment with other food. (From Stedman, 25th ed)

**Visual Cortex**: Area of the OCCIPITAL LOBE concerned with the processing of visual information relayed via VISUAL PATHWAYS.

**Geography**: 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)

**Body Size**: The physical measurements of a body.

**Probability**: The study of chance processes or the relative frequency characterizing a chance process.

**Schizophrenia**: A severe emotional disorder of psychotic depth characteristically marked by a retreat from reality with delusion formation, HALLUCINATIONS, emotional disharmony, and regressive behavior.

**Drug Costs**: 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).

**Biodiversity**: The variety of all native living organisms and their various forms and interrelationships.

**Forecasting**: 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.

**Weight Gain**: Increase in BODY WEIGHT over existing weight.

**Outpatients**: Persons who receive ambulatory care at an outpatient department or clinic without room and board being provided.

**Sequence Analysis, RNA**: A multistage process that includes cloning, physical mapping, subcloning, sequencing, and information analysis of an RNA SEQUENCE.

**Meat**: 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.

**Fruit**: The fleshy or dry ripened ovary of a plant, enclosing the seed or seeds.

**Mortality**: All deaths reported in a given population.

**Continental Population Groups**: Groups of individuals whose putative ancestry is from native continental populations based on similarities in physical appearance.

**Genomics**: The systematic study of the complete DNA sequences (GENOME) of organisms.

**Alleles**: Variant forms of the same gene, occupying the same locus on homologous CHROMOSOMES, and governing the variants in production of the same gene product.

**Cost of Illness**: 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.

**Urban Population**: The inhabitants of a city or town, including metropolitan areas and suburban areas.

**Japan**

**Brazil**

**Family**: A social group consisting of parents or parent substitutes and children.

**Acoustic Stimulation**: Use of sound to elicit a response in the nervous system.

**Emergency Service, Hospital**: Hospital department responsible for the administration and provision of immediate medical or surgical care to the emergency patient.

**Housing**: Living facilities for humans.

**Survivors**: 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.

**France**: 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.

**ROC Curve**: 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.

**Neurons**: 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.

**Reproduction**: The total process by which organisms produce offspring. (Stedman, 25th ed)

**Population Surveillance**: 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.

**Retinal Ganglion Cells**: 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.

**Occupational Exposure**: The exposure to potentially harmful chemical, physical, or biological agents that occurs as a result of one's occupation.

**Stress, Psychological**: Stress wherein emotional factors predominate.

## Effect of growth hormone treatment on adult height of children with idiopathic short stature. Genentech Collaborative Group. (1/13525)

BACKGROUND: Short-term administration of growth hormone to children with idiopathic short stature results in increases in growth rate and standard-deviation scores for height. However, the effect of long-term growth hormone therapy on adult height in these children is unknown. METHODS: We studied 121 children with idiopathic short stature, all of whom had an initial height below the third percentile, low growth rates, and maximal stimulated serum concentrations of growth hormone of at least 10 microg per liter. The children were treated with growth hormone (0.3 mg per kilogram of body weight per week) for 2 to 10 years. Eighty of these children have reached adult height, with a bone age of at least 16 years in the boys and at least 14 years in the girls, and pubertal stage 4 or 5. The difference between the predicted adult height before treatment and achieved adult height was compared with the corresponding difference in three untreated normal or short-statured control groups. RESULTS: In the 80 children who have reached adult height, growth hormone treatment increased the mean standard-deviation score for height (number of standard deviations from the mean height for chronologic age) from -2.7 to -1.4. The mean (+/-SD) difference between predicted adult height before treatment and achieved adult height was +5.0+/-5.1 cm for boys and +5.9+/-5.2 cm for girls. The difference between predicted and achieved adult height among treated boys was 9.2 cm greater than the corresponding difference among untreated boys with initial standard-deviation scores of less than -2, and the difference among treated girls was 5.7 cm greater than the difference among untreated girls. CONCLUSION: Long-term administration of growth hormone to children with idiopathic short stature can increase adult height to a level above the predicted adult height and above the adult height of untreated historical control children. (+info)## 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)###### PPT - Notes 5: Simple Linear Regression PowerPoint Presentation - ID:333739

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LogisticMultiple linear regressionGLMsHierarchical linearPredictorsStatistical modelsAnalysis of variaEstimationParametersDataBayesianPredictionCoefficientsClassical linear regression modelAlgebraEstimateCategoricalInferenceMultivariateHypothesisOptimizationFixed effectsParametricStatisticsPredictor variablesBinaryParameterDependent VariableNonlinearEstimatesEquationSimpleResponse VariableExplanatoryStatisticiansVariance componentAbstractGeneral lineaObservationsExtend

###### Logistic7

- See "Global Model Statistics for Linear Regression" and "Global Model Statistics for Logistic Regression" . (oracle.com)
- 5.Binary and Binomial data analysis: distribution and models, logistic regression models, odds ratio, one- and two-way logistic regression analysis. (manchester.ac.uk)
- Topics covered include a review of multiple linear regression and the analysis of variance, log-linear models for contingency tables, logistic regression for binary response data, Poisson regression, model selection and model checking, mixed effects models. (edu.au)
- Examples for GLMs are the logistic regression, regressions for ordinal data, or regression models for count data. (survey-data-science.net)
- Textbook examples applied linear statistical models, 4th edition linear regression logistic regression, poisson regression, and generalized linear models:, applied linear regression models 4th edition solutions searching for applied linear regression models 4th edition solutions do you really need this pdf applied. (itsrealme.com)
- Textbook examples applied linear statistical models, 4th edition linear regression logistic regression, poisson regression, and generalized linear models: applied logistic regression textbook and solutions manual pdf. (itsrealme.com)
- and kutner, applied linear statistical models, 4th edition solutions will be posted as generalized linear models (logistic regression and. (itsrealme.com)

###### Multiple linear regression1

- This course will teach you how multiple linear regression models are derived, assumptions in the models, how to test whether data meets assumptions, and develop strategies for building and understanding useful models. (statistics.com)

###### GLMs2

- The course provides an overview of generalized linear models (GLM) that encompass non-normal response distributions to model functions of the mean of Y. GLMs thus relate the expected mean E(Y) of the dependent variable to the predictor variables via a specific link function. (survey-data-science.net)
- After a very brief look at the theory for the general linear model, I will consider the case of GLMs. (edu.au)

###### Hierarchical linear2

- This course will teach you the basic theory of linear and non-linear mixed effects models, hierarchical linear models, algorithms used for estimation, primarily for models involving normally distributed errors, and examples of data analysis. (statistics.com)
- This course explains the basic theory of linear and non-linear mixed-effects models, including hierarchical linear models (HLM). (statistics.com)

###### Predictors7

- Linear models make a set of restrictive assumptions, most importantly, that the target (dependent variable y ) is normally distributed conditioned on the value of predictors with a constant variance regardless of the predicted response value. (oracle.com)
- The algorithm can build and score quality models that use a virtually limitless number of predictors (attributes). (oracle.com)
- The best regression models are those in which the predictors correlate highly with the target, but there is very little correlation between the predictors themselves. (oracle.com)
- The model describes the relationship between a dependent variable \(y\) (also called the response) as a function of one or more independent variables \(X_i\) (called the predictors). (mathworks.com)
- Thus, ANOVA can be considered as a case of a linear regression in which all predictors are categorical. (ciestateagentsltd.com)
- The term general linear model (GLM) usually refers to conventional linear regression models for a continuous response variable given continuous and/or categorical predictors. (ciestateagentsltd.com)
- The general linear model (GLM) and the generalized linear model (GLiM) are two commonly used families of statistical methods to relate some number of continuous and/or categorical predictors to a single outcome variable. (ciestateagentsltd.com)

###### Statistical models3

- The main focus of this course lies on the introduction to statistical models and estimators beyond linear regression useful to social and economic scientists. (survey-data-science.net)
- Linear models in statistics second edition alvin c. rencher and g. bruce schaalje department of statistics, 1.1 simple linear regression model 1, instructor's solutions manual pdf: applied linear statistical models solutions manual: applied linear regression solutions manual: calculus, 4th edition. (itsrealme.com)
- Student solutions manual for applied linear regression models for applied linear regression models book pdf linear statistical models fourth edition. (itsrealme.com)

###### Analysis of varia1

- Linear models include both regression and analysis of variance which are some of the most commonly applied statistical methods. (uio.no)

###### Estimation7

- They will learn basic specifications of linear mixed effects models, techniques for estimation and hypothesis testing, and basic concepts of nonlinear mixed effects models. (statistics.com)
- Description Robust estimation of linear mixed effects models, for hierarchical nested and non-nested, e.g., crossed, datasets. (henit.ie)
- Abstract: The task of robust linear estimation in the presence of outliers is of particular importance in signal processing, statistics and machine learning. (henit.ie)
- For training purposes, I was looking for a way to illustrate some of the different properties of two different robust estimation methodsfor linear regression models. (henit.ie)
- Robust linear model estimation using RANSAC - Python implementation Posted on June 10, 2014 by salzis RANSAC or "RANdom SAmple Consensus" is an iterative method to estimate parameters of a mathematical model from a set of observed data which contains outliers. (henit.ie)
- In addition, we use the stochastic model post-estimation method to verify whether the stochastic model is accurate, whether the front-difference is reasonable, and whether the re-evaluation of the parameters is reasonable by observing the measurement. (cd-biosciences.com)
- The first two units are dedicated to an introduction to maximum likelihood estimation while the rest of the units will then discuss generalized linear models (GLM) for binary choice decisions (Logit, Probit), ordinal dependent variables, and count data (Poisson, Negative Binomial). (survey-data-science.net)

###### Parameters3

- The number of regressors p less We define a t likelihood for the response variable, y, and suitable vague priors on all the model parameters: normal for α and β, half-normal for σ and gamma for ν. (henit.ie)
- This function is a linear combination of one or more model parameters called regression coefficients. (cd-biosciences.com)
- It is demonstrated that parameters are best interpretable when they represent the effects specified in the design matrix of the model. (unthsc.edu)

###### Data21

- Parametric models make assumptions about the distribution of the data. (oracle.com)
- Oracle Data Mining GLM models are easy to interpret. (oracle.com)
- In this module we discuss how to analyse dependent data, that is, data for which the assumption of independence needed in Linear Models is violated. (wur.nl)
- In the course we look upon sensory data and longitudinal medical data as the main applications and as illustrations of the general models.These models and the theory connected to them have a wide range of other applications as well. (uio.no)
- A key feature of mixed models is that, by introducing random effects in addition to fixed effects, they allow you to address multiple sources of variation when analyzing correlated data. (statistics.com)
- As an important modelling strategy Linear Models is concerned with investigating whether, and how, one or more so-called explanatory variables, such as age, sex, blood pressure, etc., influence a response variable, such as a patient's diagnosis, by taking random variations of data into account. (manchester.ac.uk)
- 6.Poisson count data analysis: Poisson regression models with offset, two-dimensional contingency tables, log-linear models. (manchester.ac.uk)
- The use of Linear Mixed-effects Models (LMMs) is set to dominate statistical analyses in psychological science and may become the default approach to analyzing quantitative data. (lancs.ac.uk)
- This object contains lots of information about your regression model, including the data used to fit the model, the specification of the model, the fitted values and residuals, etc. (datacamp.com)
- Both the robust regression models succeed in resisting the influence of the outlier point and capturing the trend in the remaining data. (henit.ie)
- Now that we have our data ready, we can build models for robust regression. (henit.ie)
- This course is intended to introduce students to generalised linear modelling methods, with emphasis on, but not limited to, common methods for analyzing categorical data. (edu.au)
- To create a linear model that fits curves and surfaces to your data, see Curve Fitting Toolbox . (mathworks.com)
- To create linear models of dynamic systems from measured input-output data, see System Identification Toolbox . (mathworks.com)
- It is a layered linear model, and the analyzed data is extracted from different hierarchies, and the differences are related to the hierarchical structure. (cd-biosciences.com)
- Here we use the variance component model to determine the correlation between the two variables based on the customer's data analysis needs. (cd-biosciences.com)
- In a data example, the relationships among race of defendant, race of victim, and death penalty sentence are examined using a log-linear model with all three two-way interactions. (unthsc.edu)
- It is always a good idea to begin any statistical modeling with a graphical assessment of the data. (methodsconsultants.com)
- To fit a linear-mixed effects model, your data must be in a properly formatted dataset array. (mathworks.com)
- Generalized) Linear models make some strong assumptions concerning the data structure:Independance of each data points.Correct distribution of the residuals.Correct specification of the variance structure.Linear relationship between the response and the linear predictor. (ciestateagentsltd.com)
- Interpret the key results for One-Way ANOVAStep 1: Determine whether the differences between group means are statistically significant.Step 2: Examine the group means.Step 3: Compare the group means.Step 4: Determine how well the model fits your data.Step 5: Determine whether your model meets the assumptions of the analysis. (ciestateagentsltd.com)

###### Bayesian2

- Additional topics may include Bayesian analysis for generalized linear models and generalized mixed effect models. (edu.au)
- In a nutshell, this model is a combination of frequency and Bayesian models. (cd-biosciences.com)

###### Prediction1

- SQL function to obtain the confidence bounds of a model prediction. (oracle.com)

###### Coefficients2

- Transparency is also a key feature: model details describe key characteristics of the coefficients, and global details provide high-level statistics. (oracle.com)
- If you generate a regression model in Spotfire you will get a table of coefficients (consisting of columns Estimate, stdError, t.value and p.value and rows corresponding to your predictor columns). (tibco.com)

###### Classical linear regression model1

- A good understanding of the classical linear regression model is a prerequisite and required for the course. (survey-data-science.net)

###### Algebra1

- Knowledge in linear algebra and calculus is useful. (survey-data-science.net)

###### Estimate1

- 2017). Estimate a robust linear model via iteratively reweighted least squares given a robust criterion estimator. (henit.ie)

###### Categorical2

- Log-linear models are used to examine joint distributions of categorical variables, dependency relations, and association patterns. (unthsc.edu)
- General linear modeling in SPSS for Windows The general linear model (GLM) is a flexible statistical model that incorporates normally distributed dependent variables and categorical or continuous independent variables. (ciestateagentsltd.com)

###### Inference1

- This course, the second of a three-course sequence, will teach you the use of inference and association through a series of practical applications, based on the resampling/simulation approach, and how to test hypotheses, compute confidence intervals regarding proportions or means, computer correlations, and use of simple linear regressions. (statistics.com)

###### Multivariate1

- For multiple and multivariate linear regression, see Statistics and Machine Learning Toolbox . (mathworks.com)

###### Hypothesis1

- What hypothesis about them correspond to the models of independence we already know? (psu.edu)

###### Optimization1

- Linear programming - (LP, or linear optimization) is a mathematical method for determining a way to achieve the best outcome (such as maximum profit or lowest cost) in a given mathematical model for some list of requirements represented as linear relationships. (academic.ru)

###### Fixed effects2

- Fit a linear mixed-effects model for miles per gallon in the city, with fixed effects for horsepower, and uncorrelated random effect for intercept and horsepower grouped by the engine type. (mathworks.com)
- It includes multiple linear regression, as well as ANOVA and ANCOVA (with fixed effects only). (ciestateagentsltd.com)

###### Parametric3

- GLM is a parametric modeling technique. (oracle.com)
- When the assumptions are met, parametric models can be more efficient than non-parametric models. (oracle.com)
- For this reason, quality diagnostics are key to developing quality parametric models. (oracle.com)

###### Statistics4

- Each model build generates many statistics and diagnostics. (oracle.com)
- In statistics, the term linear model is used in different ways according to the context. (cosmolearning.org)
- In statistics, a regression model is a mathematical model for quantitatively describing statistical relationships. (cd-biosciences.com)
- We will also learn additional statistics, besides the usual X 2 and G 2 , to assess the model fit, and to choose the "best" model. (psu.edu)

###### Predictor variables3

- Linear models describe a continuous response variable as a function of one or more predictor variables. (mathworks.com)
- Suppose that one plans to collect information from an experiment in which the response variable will be analyzed using a Generalized Linear Model (GLM), and the population parameter of interest is thought to depend on one or more continuous predictor variables. (edu.au)
- Regression is the statistical model that you use to predict a continuous outcome on the basis of one or more continuous predictor variables. (ciestateagentsltd.com)

###### Binary1

- Although very useful, the general liner model (linear regression) is not appropriate if the range of the dependent variable Y is restricted (e.g., binary, ordinal, count) and/or the variance of Y depends on the mean of Y. Generalized linear models extend the general linear model to address both of these shortcomings. (survey-data-science.net)

###### Parameter3

- where \(\beta\) represents linear parameter estimates to be computed and \(\epsilon\) represents the error terms. (mathworks.com)
- Parameter interpretation is illustrated first for a standard hierarchical model, and then for a nonstandard model that includes structural zeros. (unthsc.edu)
- GLM VERSUS REG Remember that the main difference between REG and GLM is that GLM didn't produce parameter estimates and couldn't run multiple model statements. (ciestateagentsltd.com)

###### Dependent Variable1

- Simple Linear Regression is a regression algorithm that shows the relationship between a single independent variable and a dependent variable. (codesource.io)

###### Nonlinear2

- Extending linear models through nonlinear transforms. (dnatube.com)
- To create a linear model for control system design from a nonlinear Simulink model, see Simulink Control Design . (mathworks.com)

###### Estimates1

- Coefficient estimates for robust multiple linear regression, returned as a numeric vector. (henit.ie)

###### Equation1

- 34, No. The general equation for a linear model is: \[y = \beta_0 + \sum \ \beta_i X_i + \epsilon_i\] The robust beauty of improper linear models in decision making. (henit.ie)

###### Simple6

- The link function transforms the target range to potentially -infinity to +infinity so that the simple form of linear models can be maintained. (oracle.com)
- Simple linear regression is commonly done in MATLAB . (mathworks.com)
- This tutorial shows how to fit a simple regression model (that is, a linear regression with a single independent variable) using R. The details of the underlying calculations can be found in our simple regression tutorial . (methodsconsultants.com)
- In this guide, we will learn how to build a Simple Linear Regression Model using Sci-kit Learn. (codesource.io)
- We will build a model to predict sales revenue from the advertising dataset using simple linear regression. (codesource.io)
- So we will use just the TV feature to build our simple linear regression model since it has the highest correlation with Sales. (codesource.io)

###### Response Variable1

- To study an important aspect of modern statistical modelling in an integrated way, and to develop the properties and uses of GLM, focusing on those situations in which the response variable is discrete. (manchester.ac.uk)

###### Explanatory1

- In Linear Models, linear regression technique and Normal distribution are used to explore the possible linear relation between a continuous response and one or more explanatory variables. (manchester.ac.uk)

###### Statisticians1

- Our statisticians will develop the most suitable regression model for you based on your experimental needs. (cd-biosciences.com)

###### Variance component2

- A regression model in which the independent variable is a random variable is called a random effect model (variance component model). (cd-biosciences.com)
- For variance component and linear model analysis, the following is an introduction of our work. (cd-biosciences.com)

###### Abstract1

- abstract = "This article describes log-linear models as special cases of generalized linear models. (unthsc.edu)

###### General linea7

- General linear model - Not to be confused with generalized linear model. (academic.ru)
- The general linear model (GLM) is a statistical linear model. (academic.ru)
- Question: Is Anova A General Linear Model? (ciestateagentsltd.com)
- What is univariate general linear model? (ciestateagentsltd.com)
- What is general linear model in SPSS? (ciestateagentsltd.com)
- What does a general linear model show? (ciestateagentsltd.com)
- What is general linear model used for? (ciestateagentsltd.com)

###### Observations2

- With mixed linear models a more appropriate model, allowing for dependence between observations, can be specified, which will lead to more reasonable conclusions. (wur.nl)
- Here we are looking at a scatterplot of our observations, and we've also requested the best linear fit (i.e. the regression line) to better see the positive relationship. (methodsconsultants.com)

###### Extend2

- Generalized Linear Models (GLM) include and extend the class of linear models described in "Linear Regression" . (oracle.com)
- In this section we will extend the concepts we learned about log-linear models for two-way tables to three-way tables. (psu.edu)