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.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.Odds Ratio: The ratio of two odds. The exposure-odds ratio for case control data is the ratio of the odds in favor of exposure among cases to the odds in favor of exposure among noncases. The disease-odds ratio for a cohort or cross section is the ratio of the odds in favor of disease among the exposed to the odds in favor of disease among the unexposed. The prevalence-odds ratio refers to an odds ratio derived cross-sectionally from studies of prevalent cases.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.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.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.Biostatistics: The application of STATISTICS to biological systems and organisms involving the retrieval or collection, analysis, reduction, and interpretation of qualitative and quantitative data.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.Socioeconomic Factors: Social and economic factors that characterize the individual or group within the social structure.United StatesROC 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.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.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.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.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.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.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.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)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.Smoking: Inhaling and exhaling the smoke of burning TOBACCO.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.Time Factors: Elements of limited time intervals, contributing to particular results or situations.JapanHealth Surveys: A systematic collection of factual data pertaining to health and disease in a human population within a given geographic area.Longitudinal Studies: Studies in which variables relating to an individual or group of individuals are assessed over a period of time.Pregnancy: The status during which female mammals carry their developing young (EMBRYOS or FETUSES) in utero before birth, beginning from FERTILIZATION to BIRTH.Probability: The study of chance processes or the relative frequency characterizing a chance process.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.Residence Characteristics: Elements of residence that characterize a population. They are applicable in determining need for and utilization of health services.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.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.Infant, Newborn: An infant during the first month after birth.Epidemiologic Methods: Research techniques that focus on study designs and data gathering methods in human and animal populations.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.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)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.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.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.Hospital Mortality: A vital statistic measuring or recording the rate of death from any cause in hospitalized populations.ItalyFood Microbiology: The presence of bacteria, viruses, and fungi in food and food products. This term is not restricted to pathogenic organisms: the presence of various non-pathogenic bacteria and fungi in cheeses and wines, for example, is included in this concept.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.BrazilEducational Status: Educational attainment or level of education of individuals.Prognosis: A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations.European Continental Ancestry Group: Individuals whose ancestral origins are in the continent of Europe.Genetic Predisposition to Disease: A latent susceptibility to disease at the genetic level, which may be activated under certain conditions.China: A country spanning from central Asia to the Pacific Ocean.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.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.Data Interpretation, Statistical: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.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.Health Status: The level of health of the individual, group, or population as subjectively assessed by the individual or by more objective measures.Ethnic Groups: A group of people with a common cultural heritage that sets them apart from others in a variety of social relationships.Genotype: The genetic constitution of the individual, comprising the ALLELES present at each GENETIC LOCUS.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.Alcohol Drinking: Behaviors associated with the ingesting of alcoholic beverages, including social drinking.Risk: The probability that an event will occur. It encompasses a variety of measures of the probability of a generally unfavorable outcome.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.African Americans: Persons living in the United States having origins in any of the black groups of Africa.Chi-Square Distribution: A distribution in which a variable is distributed like the sum of the squares of any given independent random variable, each of which has a normal distribution with mean of zero and variance of one. The chi-square test is a statistical test based on comparison of a test statistic to a chi-square distribution. The oldest of these tests are used to detect whether two or more population distributions differ from one another.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)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).Occupational Exposure: The exposure to potentially harmful chemical, physical, or biological agents that occurs as a result of one's occupation.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.Life Style: Typical way of life or manner of living characteristic of an individual or group. (From APA, Thesaurus of Psychological Index Terms, 8th ed)Data Collection: Systematic gathering of data for a particular purpose from various sources, including questionnaires, interviews, observation, existing records, and electronic devices. The process is usually preliminary to statistical analysis of the data.Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.Polymorphism, Single Nucleotide: A single nucleotide variation in a genetic sequence that occurs at appreciable frequency in the population.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).Breast Neoplasms: Tumors or cancer of the human BREAST.Hypertension: Persistently high systemic arterial BLOOD PRESSURE. Based on multiple readings (BLOOD PRESSURE DETERMINATION), hypertension is currently defined as when SYSTOLIC PRESSURE is consistently greater than 140 mm Hg or when DIASTOLIC PRESSURE is consistently 90 mm Hg or more.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.Polymorphism, Genetic: The regular and simultaneous occurrence in a single interbreeding population of two or more discontinuous genotypes. The concept includes differences in genotypes ranging in size from a single nucleotide site (POLYMORPHISM, SINGLE NUCLEOTIDE) to large nucleotide sequences visible at a chromosomal level.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.Survival Analysis: A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function.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.Computer Simulation: Computer-based representation of physical systems and phenomena such as chemical processes.

*  How the logistic regression model works
... we are going to learn how logistic regression model works along with the key role of softmax function and the implementation in ... How to implement logistic regression model in python for binary classification * How Multinomial Logistic Regression Model ... let's brush up the logistic regression understanding level with an example.. Logistic Regression Model Example. logistic ... Let's understand the above logistic regression model definition word by word. What logistic regression model will do is, It ...
*  IT Perspectives 2007: Logistics IT Market Insight Survey - Inbound Logistics
Their answers provide an in-depth look at the state of the logistics IT market. ... IL's exclusive research polls IT providers to gauge their perspectives on logistics IT challenges, solutions, and opportunities ... "Across all segments, we have seen a move toward both an on-demand delivery model, and for systems that can adapt to changing ... Global Logistics RFP*Sustainable Supply Chain Partner RFP*Latin America RFP*Logistics IT RFP*Logistics Planner RFP*Materials ...
*  Ch5-4 - Outline 5.1 Interpreting Parameters in Logistic Regression Chapter 5 Logistic Regression 5.2 Inference for Logistic...
Logistic Regression 5.2 Inference for Logistic Regression Deyuan Li ... Outline 5.1 Interpreting Parameters in Logistic Regression Chapter 5. ... 5.3 Logit Models with Categorical Predictors • 5.4 Multiple Logistic Regression • 5.5 Fitting Logistic Regression Models 2 / ... Statistics 659 4 Logistic Regression Model Logistic regression is a technique for rel ...
*  Linear Logistic Models with Relaxed Assumptions in R | SpringerLink
... are a flexible tool for item-based measurement of change or multidimensional Rasch models. Their key features are to allow for ... Fischer, G. (1993). Linear logistic models for change. In G. Fischer & I. Molenaar (Eds.), Rasch models: Foundations, recent ... Linear logistic models with relaxed assumptions (LLRA) are a flexible tool for item-based measurement of change or ... Rusch T., Maier M.J., Hatzinger R. (2013) Linear Logistic Models with Relaxed Assumptions in R. In: Lausen B., Van den Poel D ...
*  R: Four-parameter Logistic Model
Four-parameter Logistic Model. Description. This selfStart. model evaluates the four-parameter logistic function and its ... a numeric vector of values at which to evaluate the model.. A. a numeric parameter representing the horizontal asymptote on the ...
*  Logistic Model with Harvesting Questions
... Hey Guys,. This is my first time posting on here. I'm catching up on some first year ... Solving Unknowns in a Logistic Growth Model. Posted in the Pre-Calculus Forum ...
*  A ballooned beta-logistic model
... expected responses follow a logistic function which can be made equal to that of the Four Parameter Logistic (4PL) model. But ... The Ballooned Beta-logistic (BBL) model expands the response boundaries from (0,1) to (L,U), where L and U are unknown ... We show the BBL model has advantages over the 4PL model. ... The beta distribution is a simple and flexible model in which ... In contrast, the BBL model naturally has bounded responses and inhomogeneous variance. The asymptotic normality of maximum ...
*  Logistic Models for Symbiosis, Predator-Prey, and Competition: Media & Communications Book Chapter | IGI Global
... is supposed to evolve following the logistic mapping, then we are tempted to think that the dynamics of two species ... Logistic Models for Symbiosis, Predator-Prey, and Competition: 10.4018/978-1-59904-885-7.ch111: If one isolated species ( ... three different models are obtained. Each model is a cubic two-dimensional discrete logistic-type equation with its own ... "Logistic Models for Symbiosis, Predator-Prey, and Competition." In Encyclopedia of Networked and Virtual Organizations, ed. ...
*  R] Plot of odds ratios obtained from a logistic model
Could you help me? Is there any option when modelling the logistic model in R? Thank you in advance *Previous message: [R] ... R] Plot of odds ratios obtained from a logistic model. gepeto geppetto5st at gmail.com Sat Feb 6 19:28:54 CET 2010 *Previous ... Hi all! I am trying to develop a plot a figure in which I would like to show the odds ratios obtained from a logistic model. I ... Next message: [R] Plot of odds ratios obtained from a logistic model ...
*  JAFLME - Joint Automated Field Logistics Model for Employment | AcronymFinder
JAFLME stands for Joint Automated Field Logistics Model for Employment. JAFLME is defined as Joint Automated Field Logistics ... How is Joint Automated Field Logistics Model for Employment abbreviated? ... www.acronymfinder.com/Joint-Automated-Field-Logistics-Model-for-Employment-(JAFLME).html',JAFLME,/a,. ... www.acronymfinder.com/Joint-Automated-Field-Logistics-Model-for-Employment-(JAFLME).html ...
*  Logistic model - Wikipedia
Logistic model may refer to: Logistic function - a continuous sigmoidal curve Logistic map - a discrete version, which exhibits ...
*  Stata Modules for Calculating Novel Predictive Performance Indices for Logistic Models
... Barkhordari, Mahnaz Department of ... The command is addpred for logistic regression models.Conclusions: The Stata package provided herein can encourage the use of ... Parallel with predictive models development, biomarker researches emerged in an impressively great scale. The key question is ... for logistic-based regression analyses.We applied the commands to a real data on women participating the Tehran lipid and ...
*  Logistic model tree - Wikipedia
Logistic model trees are based on the earlier idea of a model tree: a decision tree that has linear regression models at its ... a logistic model tree (LMT) is a classification model with an associated supervised training algorithm that combines logistic ... Niels Landwehr, Mark Hall, and Eibe Frank (2003). Logistic model trees (PDF). ECML PKDD. CS1 maint: Uses authors parameter ( ... doi:10.1007/s10994-005-0466-3. Sumner, Marc, Eibe Frank, and Mark Hall (2005). Speeding up logistic model tree induction (PDF ...
*  Comparing consumer preferences for color and nutritional quality in maize: Application of a semi-double-bound logistic model on...
Urban consumers' willingness to pay (WTP) for yellow maize was estimated, using a semi-double-bounded logistic model, based on ... "Comparing consumer preferences for color and nutritional quality in maize: Application of a semi-double-bound logistic model on ... Urban consumers' willingness to pay (WTP) for yellow maize was estimated, using a semi-double-bounded logistic model, based on ... Comparing consumer preferences for color and nutritional quality in maize: Application of a semi-double-bound logistic model on ...
*  Equivalent linear logistic test models | SpringerLink
We demonstrate that there are infinitely many equivalent ways to specify a model. An implication is that there may well be many ... This paper is about the Linear Logistic Test Model (LLTM). ... Fischer, G.H. (1995). The linear logistic test model. In G.H. ... This paper is about the Linear Logistic Test Model (LLTM). We demonstrate that there are infinitely many equivalent ways to ... Bechger, T.M., Verhelst, N.D., & Verstralen, H.F.M. (2001). Identifiability of nonlinear logistic test models.Psychometrika, 66 ...
*  The Interport: A Logistics Model and an Application to the Distribution of Maritime Containers: Business & Management Journal...
In a container transportation and logistics network, an interport is a common user facility located in the hinterland of one or ... A Logistics Model and an Application to the Distribution of Maritime Containers: 10.4018/jisscm.2012100102: ... To analyze the resulting logistic system, we propose a novel mathematical model type: the interport model. Generically, it is ... "The Interport: A Logistics Model and an Application to the Distribution of Maritime Containers," International Journal of ...
*  City Logistics: Modelling, planning and evaluation : Eiichi Taniguchi : 9781138885455
Modelling, planning and evaluation by Eiichi Taniguchi, 9781138885455, available at Book Depository with free delivery ... He developed vehicle routing and scheduling with time windows models and multi-agent models for evaluating city logistics ... This volume on city logistics presents recent advances of modelling urban freight transport as well as planning and evaluating ... His research centres on City Logistics and urban freight modelling. ...
*  Non-Inferiority Test in Multple Logistic Model | Statistics Help @ Talk Stats Forum
Does any body have any insight or experience running a non-inferiority test based on multiple linear or logistic regression. So ... Does any body have any insight or experience running a non-inferiority test based on multiple linear or logistic regression. So ...
*  Efficient simulation of Bayesian logistic regression models
Holmes, C. und Knorr-Held, Leonhard (2003): Efficient simulation of Bayesian logistic regression models. ... In this paper we highlight a data augmentation approach to inference in the Bayesian logistic regression model. We demonstrate ... We illustrate that the method is particularly suited to problems in covariate set uncertainty and random effects models. ...
*  R: ROC Plot for a logistic regression model
rocplot(logistic.model,diag=TRUE,pred.prob.labels=FALSE,prob.label.digits=3,AUC=TRUE) Arguments. logistic.model. a glm object ... ROC Plot for a logistic regression model Description. Plots the ROC Curve ... model.glm ,- glm(formula=income,5930.5 ~ education + women + type, family=binomial(),data=Prestige,na.action=na.omit) rocplot( ... model.glm) [Package Deducer version 0.7-7 Index]. ...
*  Rasch Measurement Program Comparisons on the Linear Logistic Test Model | RTI
Kline, T., Schmidt, K., & Bowles, R. (2006). Rasch Measurement Program Comparisons on the Linear Logistic Test Model. Journal ...
*  Archives | Logistics Modeling Software
Logistics is basic for any company's alternative and furthermore crisis.. *Logistics is completely to a great degree very much ... Logistics has not been viewed as an occupation decision.. *Logistics attempts to an all inclusive position. For such huge ... "Logistics" is ordinarily mistaken for military operations. In any case, Logistics has changed into more prominent and more ... Today, Logistics has developed from military to standard society how we deal with the stream of merchandise and enterprises ...
*  NetLogo Models Library: Logistic Growth
Models:. Library. Community. Modeling Commons. User Manuals:. Web. Printable Chinese. Czech. Japanese. NetLogo Models Library: ... Sample Models/System Dynamics. (back to the library) Logistic Growth. If you download the NetLogo application, this model is ... For the model itself:. *Wilensky, U. (2005). NetLogo Logistic Growth model. http://ccl.northwestern.edu/netlogo/models/ ... RELATED MODELS. System Dynamics -, Exponential Growth. HOW TO CITE. If you mention this model or the NetLogo software in a ...
*  Decreasing power of credit risk model (logistic regression)
... Hi,. I m trying to build a credit risk model (an application ... The whole model has a power 60% which is good. But problem is that power in particular years is decreasing under the acceptable ... Would it be correct to use weighting by the variable of weights and to use logistic regression afterwards? Will weighting have ... any influence on logistic regression and its outcome?. Thanks for any advise.. Espanas. ...

QRISK: QRISK2 (the most recent version of QRISK) is a prediction algorithm for cardiovascular disease (CVD) that uses traditional risk factors (age, systolic blood pressure, smoking status and ratio of total serum cholesterol to high-density lipoprotein cholesterol) together with body mass index, ethnicity, measures of deprivation, family history, chronic kidney disease, rheumatoid arthritis, atrial fibrillation, diabetes mellitus, and antihypertensive treatment.Nested case-control study: A nested case control (NCC) study is a variation of a case-control study in which only a subset of controls from the cohort are compared to the incident cases. In a case-cohort study, all incident cases in the cohort are compared to a random subset of participants who do not develop the disease of interest.Biostatistics (journal): Biostatistics is a peer-reviewed scientific journal covering biostatistics, that is, statistics for biological and medical research. The journals that had cited Biostatistics the most by 2008Journal Citation Reports 2008, Science Edition were Biometrics, Journal of the American Statistical Association, Biometrika, Statistics in Medicine, and Journal of the Royal Statistical Society, Series B.List of Parliamentary constituencies in Kent: The ceremonial county of Kent,Inverse probability weighting: Inverse probability weighting is a statistical technique for calculating statistics standardized to a population different from that in which the data was collected. Study designs with a disparate sampling population and population of target inference (target population) are common in application.Age adjustment: In epidemiology and demography, age adjustment, also called age standardization, is a technique used to allow populations to be compared when the age profiles of the populations are quite different.Global Risks Report: The Global Risks Report is an annual study published by the World Economic Forum ahead of the Forum’s Annual Meeting in Davos, Switzerland. Based on the work of the Global Risk Network, the report describes changes occurring in the global risks landscape from year to year and identifies the global risks that could play a critical role in the upcoming year.Closed-ended question: A closed-ended question is a question format that limits respondents with a list of answer choices from which they must choose to answer the question.Dillman D.Temporal analysis of products: Temporal Analysis of Products (TAP), (TAP-2), (TAP-3) is an experimental technique for studyingNiigata UniversityPrenatal nutrition: Nutrition and weight management before and during :pregnancy has a profound effect on the development of infants. This is a rather critical time for healthy fetal development as infants rely heavily on maternal stores and nutrient for optimal growth and health outcome later in life.Negative probability: The probability of the outcome of an experiment is never negative, but quasiprobability distributions can be defined that allow a negative probability for some events. These distributions may apply to unobservable events or conditional probabilities.Budic II of Brittany: Budic II (; or ; ), formerly known as Budick, was a king of Cornouaille in Brittany in the late 5th and early 6th centuries. He was the father of Hoel Mawr and is probably to be identified with the Emyr Llydaw ("Emperor of Brittany") and King Nentres who appear in Arthurian legend.Neighbourhood: A neighbourhood (Commonwealth English), or neighborhood (American English), is a geographically localised community within a larger city, town, suburb or rural area. Neighbourhoods are often social communities with considerable face-to-face interaction among members.Regression dilution: Regression dilution, also known as regression attenuation, is the biasing of the regression slope towards zero (or the underestimation of its absolute value), caused by errors in the independent variable.Epidemiological method: The science of epidemiology has matured significantly from the times of Hippocrates and John Snow. The techniques for gathering and analyzing epidemiological data vary depending on the type of disease being monitored but each study will have overarching similarities.Incidence (epidemiology): Incidence is a measure of the probability of occurrence of a given medical condition in a population within a specified period of time. Although sometimes loosely expressed simply as the number of new cases during some time period, it is better expressed as a proportion or a rate with a denominator.Assay sensitivity: Assay sensitivity is a property of a clinical trial defined as the ability of a trial to distinguish an effective treatment from a less effective or ineffective intervention. Without assay sensitivity, a trial is not internally valid and is not capable of comparing the efficacy of two interventions.Generalizability theory: Generalizability theory, or G Theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations. It is used to determine the reliability (i.Triangle of death (Italy): The triangle of death (Italian: Triangolo della morte) is an area in the Italian province of Campania comprising the municipalities of Acerra, Nola and Marigliano. The region has recently experienced increasing deaths caused by cancer and other diseases that exceeds the Italian national average.University of CampinasLayout of the Port of Tianjin: The Port of Tianjin is divided into nine areas: the three core (“Tianjin Xingang”) areas of Beijiang, Nanjiang, and Dongjiang around the Xingang fairway; the Haihe area along the river; the Beitang port area around the Beitangkou estuary; the Dagukou port area in the estuary of the Haihe River; and three areas under construction (Hanggu, Gaoshaling, Nangang).Decoding methods: In coding theory, decoding is the process of translating received messages into codewords of a given code. There have been many common methods of mapping messages to codewords.Comorbidity: In medicine, comorbidity is the presence of one or more additional disorders (or diseases) co-occurring with a primary disease or disorder; or the effect of such additional disorders or diseases. The additional disorder may also be a behavioral or mental disorder.Self-rated health: Self-rated health (also called Self-reported health, Self-assessed health, or perceived health) refers to both a single question such as “in general, would you say that you health is excellent, very good, good, fair, or poor?” and a survey questionnaire in which participants assess different dimensions of their own health.Matrix model: == Mathematics and physics ==Alcohol and cardiovascular disease: Excessive alcohol intake is associated with an elevated risk of alcoholic liver disease (ALD), heart failure, some cancers, and accidental injury, and is a leading cause of preventable death in industrialized countries. However, extensive research has shown that moderate alcohol intake is associated with health benefits, including less cardiovascular disease, diabetes, hypertension, and lower all-cause mortality.Von Neumann regular ring: In mathematics, a von Neumann regular ring is a ring R such that for every a in R there exists an x in R such that . To avoid the possible confusion with the regular rings and regular local rings of commutative algebra (which are unrelated notions), von Neumann regular rings are also called absolutely flat rings, because these rings are characterized by the fact that every left module is flat.African-American family structure: The family structure of African-Americans has long been a matter of national public policy interest.Moynihan's War on Poverty report A 1965 report by Daniel Patrick Moynihan, known as The Moynihan Report, examined the link between black poverty and family structure.Classification of obesity: Obesity is a medical condition in which excess body fat has accumulated to the extent that it has an adverse effect on health.WHO 2000 p.Occupational hygiene: Occupational (or "industrial" in the U.S.Regularized canonical correlation analysis: Regularized canonical correlation analysis is a way of using ridge regression to solve the singularity problem in the cross-covariance matrices of canonical correlation analysis. By converting \operatorname{cov}(X, X) and \operatorname{cov}(Y, Y) into \operatorname{cov}(X, X) + \lambda I_X and \operatorname{cov}(Y, Y) + \lambda I_Y, it ensures that the above matrices will have reliable inverses.Clonal Selection Algorithm: In artificial immune systems, Clonal selection algorithms are a class of algorithms inspired by the clonal selection theory of acquired immunity that explains how B and T lymphocytes improve their response to antigens over time called affinity maturation. These algorithms focus on the Darwinian attributes of the theory where selection is inspired by the affinity of antigen-antibody interactions, reproduction is inspired by cell division, and variation is inspired by somatic hypermutation.WGAViewer: WGAViewer is a bioinformatics software tool which is designed to visualize, annotate, and help interpret the results generated from a genome wide association study (GWAS). Alongside the P values of association, WGAViewer allows a researcher to visualize and consider other supporting evidence, such as the genomic context of the SNP, linkage disequilibrium (LD) with ungenotyped SNPs, gene expression database, and the evidence from other GWAS projects, when determining the potential importance of an individual SNP.Management of HIV/AIDS: The management of HIV/AIDS normally includes the use of multiple antiretroviral drugs in an attempt to control HIV infection. There are several classes of antiretroviral agents that act on different stages of the HIV life-cycle.Breast cancer classification: Breast cancer classification divides breast cancer into categories according to different schemes, each based on different criteria and serving a different purpose. The major categories are the histopathological type, the grade of the tumor, the stage of the tumor, and the expression of proteins and genes.HypertensionBiomarkers of aging: Biomarkers of aging are biomarkers that better predict functional capacity at a later age than chronological age. Stated another way, biomarkers of aging would give the true "biological age", which may be different from the chronological age.Gene polymorphismInterval boundary element method: Interval boundary element method is classical boundary element method with the interval parameters.

(1/24374) Analysis of the effect of conversion from open to closed surgical intensive care unit.

OBJECTIVE: To compare the effect on clinical outcome of changing a surgical intensive care unit from an open to a closed unit. DESIGN: The study was carried out at a surgical intensive care unit in a large tertiary care hospital, which was changed on January 1, 1996, from an open unit, where private attending physicians contributed and controlled the care of their patients, to a closed unit, where patients' medical care was provided only by the surgical critical care team (ABS or ABA board-certified intensivists). A retrospective review was undertaken over 6 consecutive months in each system, encompassing 274 patients (125 in the open-unit period, 149 in the closed-unit period). Morbidity and mortality were compared between the two periods, along with length-of-stay (LOS) and number of consults obtained. A set of independent variables was also evaluated, including age, gender, APACHE III scores, the presence of preexisting medical conditions, the use of invasive monitoring (Swan-Ganz catheters, central and arterial lines), and the use of antibiotics, low-dose dopamine (LDD) for renal protection, vasopressors, TPN, and enteral feeding. RESULTS: Mortality (14.4% vs. 6.04%, p = 0.012) and the overall complication rate (55.84% vs. 44.14%, p = 0.002) were higher in the open-unit group versus the closed-unit group, respectively. The number of consults obtained was decreased (0.6 vs. 0.4 per patient, p = 0.036), and the rate of occurrence of renal failure was higher in the open-unit group (12.8% vs. 2.67%, p = 0.001). The mean age of the patients was similar in both groups (66.48 years vs. 66.40, p = 0.96). APACHE III scores were slightly higher in the open-unit group but did not reach statistical significance (39.02 vs. 36.16, p = 0.222). There were more men in the first group (63.2% vs. 51.3%). The use of Swan-Ganz catheters or central and arterial lines were identical, as was the use of antibiotics, TPN, and enteral feedings. The use of LDD was higher in the first group, but the LOS was identical. CONCLUSIONS: Conversion of a tertiary care surgical intensive care unit from an open to closed environment reduced dopamine usage and overall complication and mortality rates. These results support the concept that, when possible, patients in surgical intensive care units should be managed by board-certified intensivists in a closed environment.  (+info)

(2/24374) Antiphospholipid, anti-beta 2-glycoprotein-I and anti-oxidized-low-density-lipoprotein antibodies in antiphospholipid syndrome.

Antiphospholipid antibodies (aPL), anti-beta 2-glycoprotein I (anti-beta 2-GPI) and anti-oxidized-low-density lipoprotein (LDL) antibodies are all implicated in the pathogenesis of antiphospholipid syndrome. To investigate whether different autoantibodies or combinations thereof produced distinct effects related to their antigenic specificities, we examined the frequencies of antiphospholipid syndrome (APS)-related features in the presence of different antibodies [aPL, beta 2-GPI, anti-oxidized low density lipoprotein (LDL)] in 125 patients with APS. Median follow-up was 72 months: 58 patients were diagnosed as primary APS and 67 as APS plus systemic lupus erythematosus (SLE). Anticardiolipin antibodies (aCL), anti-beta 2-GPI and anti-oxidized LDL antibodies were determined by ELISA; lupus anticoagulant (LA) by standard coagulometric methods. Univariate analysis showed that patients positive for anti-beta 2-GPI had a higher risk of recurrent thrombotic events (OR = 3.64, 95% CI, p = 0.01) and pregnancy loss (OR = 2.99, 95% CI, p = 0.004). Patients positive for anti-oxidized LDL antibodies had a 2.24-fold increase in the risk of arterial thrombosis (2.24, 95% CI, p = 0.03) and lower risk of thrombocytopenia (OR = 0.41 95% CI, p = 0.04). Patients positive for aCL antibodies had a higher risk of pregnancy loss (OR = 4.62 95% CI, p = 0.001). When these data were tested by multivariate logistic regression, the association between anti-beta 2-GPI and pregnancy loss and the negative association between anti-oxidized LDL antibodies and thrombocytopenia disappeared.  (+info)

(3/24374) Capture-recapture models including covariate effects.

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)

(4/24374) Risk factors for injuries and other health problems sustained in a marathon.

OBJECTIVES: To identify risk factors for injuries and other health problems occurring during or immediately after participation in a marathon. METHODS: A prospective cohort study was undertaken of participants in the 1993 Auckland Citibank marathon. Demographic data, information on running experience, training and injuries, and information on other lifestyle factors were obtained from participants before the race using an interviewer-administered questionnaire. Information on injuries and other health problems sustained during or immediately after the marathon were obtained by a self administered questionnaire. Logistic regression analyses were undertaken to identify significant risk factors for health problems. RESULTS: This study, one of only a few controlled epidemiological studies that have been undertaken of running injuries, has identified a number of risk factors for injuries and other health problems sustained in a marathon. Men were at increased risk of hamstring and calf problems, whereas women were at increased risk of hip problems. Participation in a marathon for the first time, participation in other sports, illness in the two weeks before the marathon, current use of medication, and drinking alcohol once a month or more, were associated with increased self reported risks of problems. While increased training seemed to increase the risk of front thigh and hamstring problems, it may decrease the risk of knee problems. There are significant but complex relations between age and risk of injury or health problem. CONCLUSIONS: This study has identified certain high risk subjects and risk factors for injuries and other health problems sustained in a marathon. In particular, subjects who have recently been unwell or are taking medication should weigh up carefully the pros and cons of participating.  (+info)

(5/24374) Early mycological treatment failure in AIDS-associated cryptococcal meningitis.

Cryptococcal meningitis causes significant morbidity and mortality in persons with AIDS. Of 236 AIDS patients treated with amphotericin B plus flucytosine, 29 (12%) died within 2 weeks and 62 (26%) died before 10 weeks. Just 129 (55%) of 236 patients were alive with negative cerebrospinal fluid (CSF) cultures at 10 weeks. Multivariate analyses identified that titer of cryptococcal antigen in CSF, serum albumin level, and CD4 cell count, together with dose of amphotericin B, had the strongest joint association with failure to achieve negative CSF cultures by day 14. Among patients with similar CSF cryptococcal antigen titers, CD4 cell counts, and serum albumin levels, the odds of failure at week 10 for those without negative CSF cultures by day 14 was five times that for those with negative CSF cultures by day 14 (odds ratio, 5.0; 95% confidence interval, 2.2-10.9). Prognosis is dismal for patients with AIDS-related cryptococcal meningitis. Multivariate analyses identified three components that, along with initial treatment, have the strongest joint association with early outcome. Clearly, more effective initial therapy and patient management strategies that address immune function and nutritional status are needed to improve outcomes of this disease.  (+info)

(6/24374) The Sock Test for evaluating activity limitation in patients with musculoskeletal pain.

BACKGROUND AND PURPOSE: Assessment within rehabilitation often must reflect patients' perceived functional problems and provide information on whether these problems are caused by impairments of the musculoskeletal system. Such capabilities were examined in a new functional test, the Sock Test, simulating the activity of putting on a sock. SUBJECTS AND METHODS: Intertester reliability was examined in 21 patients. Concurrent validity, responsiveness, and predictive validity were examined in a sample of 337 patients and in subgroups of this sample. RESULTS: Intertester reliability was acceptable. Sock Test scores were related to concurrent reports of activity limitation in dressing activities. Scores also reflected questionnaire-derived reports of problems in a broad range of activities of daily living and pain and were responsive to change over time. Increases in age and body mass index increased the likelihood of Sock Test scores indicating activity limitation. Pretest scores were predictive of perceived difficulties in dressing activities after 1 year. CONCLUSION AND DISCUSSION: Sock Test scores reflect perceived activity limitations and restrictions of the musculoskeletal system.  (+info)

(7/24374) Modified cuspal relationships of mandibular molar teeth in children with Down's syndrome.

A total of 50 permanent mandibular 1st molars of 26 children with Down's syndrome (DS) were examined from dental casts and 59 permanent mandibular 1st molars of normal children were examined from 33 individuals. The following measurements were performed on both right and left molars (teeth 46 and 36 respectively): (a) the intercusp distances (mb-db, mb-d, mb-dl, db-ml, db-d, db-dl, db-ml, d-dl, d-ml, dl-ml); (b) the db-mb-ml, mb-db-ml, mb-ml-db, d-mb-dl, mb-d-dl, mb-dl-d angles; (c) the area of the pentagon formed by connecting the cusp tips. All intercusp distances were significantly smaller in the DS group. Stepwise logistic regression, applied to all the intercusp distances, was used to design a multivariate probability model for DS and normals. A model based on 2 distances only, mb-dl and mb-db, proved sufficient to discriminate between the teeth of DS and the normal population. The model for tooth 36 for example was as follows: p(DS) = (e(30.6-5.6(mb-dl)+25(mb-db)))/(1 + e(30.6 5.6(mb-dl)+25(mb db))). A similar model for tooth 46 was also created, as well as a model which incorporated both teeth. With respect to the angles, significant differences between DS and normals were found in 3 out of the 6 angles which were measured: the d-mb-dl angle was smaller than in normals, the mb-d-dl angle was higher, and the mb-dl-d angle was smaller. The dl cusp was located closer to the centre of the tooth. The change in size occurs at an early stage, while the change in shape occurs in a later stage of tooth formation in the DS population.  (+info)

(8/24374) Organizational and environmental factors associated with nursing home participation in managed care.

OBJECTIVE: To develop and test a model, based on resource dependence theory, that identifies the organizational and environmental characteristics associated with nursing home participation in managed care. DATA SOURCES AND STUDY SETTING: Data for statistical analysis derived from a survey of Directors of Nursing in a sample of nursing homes in eight states (n = 308). These data were merged with data from the On-line Survey Certification and Reporting System, the Medicare Managed Care State/County Data File, and the 1995 Area Resource File. STUDY DESIGN: Since the dependent variable is dichotomous, the logistic procedure was used to fit the regression. The analysis was weighted using SUDAAN. FINDINGS: Participation in a provider network, higher proportions of resident care covered by Medicare, providing IV therapy, greater availability of RNs and physical therapists, and Medicare HMO market penetration are associated with a greater likelihood of having a managed care contract. CONCLUSION: As more Medicare recipients enroll in HMOs, nursing home involvement in managed care is likely to increase. Interorganizational linkages enhance the likelihood of managed care participation. Nursing homes interested in managed care should consider upgrading staffing and providing at least some subacute services.  (+info)

  • binomial
  • For example, the case above of predicted number of beach attendees would typically be modeled with a Poisson distribution and a log link, while the case of predicted probability of beach attendance would typically be modeled with a Bernoulli distribution (or binomial distribution, depending on exactly how the problem is phrased) and a log-odds (or logit) link function. (wikipedia.org)
  • In a generalized linear model (GLM), each outcome Y of the dependent variables is assumed to be generated from a particular distribution in the exponential family, a large range of probability distributions that includes the normal, binomial, Poisson and gamma distributions, among others. (wikipedia.org)
  • function
  • The two common way of designing reverse logistics network are the Mixed Integer Linear Programing (MILP) and Mixed Integer Non-Linear Programing (MINLP) methods, where the objective function, decision variables and constraint have to be defined This model is a two-level location problem with three type of facilities, integrated forward and reverse flow of goods. (wikipedia.org)
  • Objective function: minimizing linear cost function including fix and variable costs Decision variables: location of manufacturer and distribution centeramount of production demand quantity of returned used products Constraints: satisfaction of the demand opening of facilities This model take into account just reverse flow of goods. (wikipedia.org)
  • Robust optimization: This method is calibrating the model in that way to minimize the deviation of the values of the objective function at each scenario. (wikipedia.org)
  • The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. (wikipedia.org)
  • Imagine, for example, a model that predicts the likelihood of a given person going to the beach as a function of temperature. (wikipedia.org)
  • Generalized linear models cover all these situations by allowing for response variables that have arbitrary distributions (rather than simply normal distributions), and for an arbitrary function of the response variable (the link function) to vary linearly with the predicted values (rather than assuming that the response itself must vary linearly). (wikipedia.org)
  • The logit in logistic regression is a special case of a link function in a generalized linear model: it is the canonical link function for the Bernoulli distribution. (wikipedia.org)
  • The inverse-logit function (i.e., the logistic function) is also sometimes referred to as the expit function. (wikipedia.org)
  • Closely related to the logit function (and logit model) are the probit function and probit model. (wikipedia.org)
  • In fact, the logit is the quantile function of the logistic distribution, while the probit is the quantile function of the normal distribution. (wikipedia.org)
  • assumes
  • Classical test theory assumes a state model because it is applied by determining item parameters for a sample of examinees determined to be in each category. (wikipedia.org)
  • The classification groups will need to be more or less arbitrarily defined along the continuum, such as the use of a cutscore to demarcate masters and nonmasters, but the specification of item parameters assumes a trait model. (wikipedia.org)
  • prediction model
  • The key question is how best to assess and quantify the improvement in risk prediction offered by new biomarkers or more basically how to assess the performance of a risk prediction model. (diva-portal.org)
  • As an example, a prediction model might predict that 10 degree temperature decrease would lead to 1,000 fewer people visiting the beach is unlikely to generalize well over both small beaches (e.g. those where the expected attendance was 50 at a particular temperature) and large beaches (e.g. those where the expected attendance was 10,000 at a low temperature). (wikipedia.org)
  • The problem with this kind of prediction model would imply a temperature drop of 10 degrees would lead to 1,000 fewer people visiting the beach, a beach whose expected attendance was 50 at a higher temperature would now be predicted to have the impossible attendance value of −950. (wikipedia.org)
  • simulation
  • City logistics long-term planning: simulation of shopping mobility and goods restocking and related support systems Agostino Nuzzolo, Antonio Comi and Luca Rosati 8. (bookdepository.com)
  • probabilities
  • That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which may be real-valued, binary-valued, categorical-valued, etc. (wikipedia.org)
  • likelihood
  • The asymptotic normality of maximum likelihood estimators (MLEs) is obtained even though the support of this non-regular regression model depends on unknown parameters. (umsystem.edu)
  • They proposed an iteratively reweighted least squares method for maximum likelihood estimation of the model parameters. (wikipedia.org)
  • application
  • Comparing consumer preferences for color and nutritional quality in maize: Application of a semi-double-bound logistic model on urban consumers in Kenya ," Food Policy , Elsevier, vol. 33(4), pages 362-370, August. (repec.org)
  • Application of exact route optimization for the evaluation of a city logistics truck ban scheme Ali Gul Qureshi, Eiichi Taniguchi, Russell G. Thompson and Joel S.E. Teo 3. (bookdepository.com)
  • Model of debris collection operation after disasters and its application in urban area Andie Pramudita and Eiichi Taniguchi 9. (bookdepository.com)
  • If you download the NetLogo application , this model is included. (northwestern.edu)
  • efficient
  • As city logistics aims at creating efficient and environmental-friendly urban freight transport systems, these chapters deal with challenging urban freight transport problems from various point of views of the usage of ITS (Intelligent Transport Systems), multi-agent modelling, public-private partnerships, and the disaster consideration. (bookdepository.com)
  • method
  • We illustrate that the method is particularly suited to problems in covariate set uncertainty and random effects models. (uni-muenchen.de)
  • advantages
  • We show the BBL model has advantages over the 4PL model. (umsystem.edu)
  • The model highlights the advantages that shippers may enjoy in routing their containers from the seaports to their final hinterland destinations via one or several interports. (igi-global.com)
  • distribution
  • The beta distribution is a simple and flexible model in which responses are naturally confined to the finite interval (0,1). (umsystem.edu)
  • The huge expansion in international trade during the last 50 years (facilitated and propelled by the invention of the standardized container as a medium of transport) has led to overcrowding of port facilities world-wide and growing pains in logistic systems handling the customs examination, storage and distribution of containers. (igi-global.com)
  • In this model the products are gathered from the consumers and transferred back to the producers, hence the direction of the flow in the distribution supply chain is reversed and the model is expanded with the recovery center. (wikipedia.org)
  • 1987
  • Criminologist Lynch (1987), using "domain-specific" models, demonstrates that occupation-related activities generally have a stronger impact on the risk of victimization at work than sociodemographic characteristics. (wikipedia.org)
  • responses
  • In this paper we introduce and illustrate new functionality from the R package eRm for fitting, comparing and plotting of LLRA models for dichotomous and polytomous responses with any number of time points, treatment groups and categorical covariates. (springer.com)
  • In contrast, the BBL model naturally has bounded responses and inhomogeneous variance. (umsystem.edu)
  • Binary
  • For the binary case, a common approach is to apply Platt scaling, which learns a logistic regression model on the scores. (wikipedia.org)
  • This allows the choice of K alternatives to be modeled as a set of K-1 independent binary choices, in which one alternative is chosen as a "pivot" and the other K-1 compared against it, one at a time. (wikipedia.org)
  • collaboration
  • We also propose that these models could be useful for thinking in the different interactions happening in the economic world, as for instance for the competition and the collaboration between corporations. (igi-global.com)
  • Collaboration in urban logistics: motivations and barriers Lindawati, Johan van Schagen, Mark Goh and Robert de Souza 12. (bookdepository.com)
  • methods
  • Discrimination, calibration, and added predictive value have been recently suggested to be used while comparing the predictive performances of the predictive models' with and without novel biomarkers.Objectives: Lack of user-friendly statistical software has restricted implementation of novel model assessment methods while examining novel biomarkers. (diva-portal.org)
  • change
  • Extending rating scale and partial credit model for assessing change. (springer.com)
  • An implication is that there may well be many ways to change the specification of a given LLTM and achieve the same improvement in model fit. (springer.com)
  • A reasonable model might predict, for example, that a change in 10 degrees makes a person two times more or less likely to go to the beach. (wikipedia.org)
  • analysis
  • The overparameterized analysis of variance Model. (springer.com)
  • Equivalent models in covariance structure analysis. (springer.com)
  • The main objective is to maximize profit by determining the optimal number of facilities in order to: collection point be close to the consumers returning process be simple collection period be appropriate Sensitivity analysis: Through sensitivity analysis it can be tested how the output of the model will be changed if the decision variables such as the returned amount, number of disassembly and cost are varying. (wikipedia.org)
  • items
  • It means that the used items are gathered from consumers, transported back to plants and after remanufacturing get into the logistics network of new products. (wikipedia.org)
  • In most contexts, the parameters of the model characterize the proficiency of the respondents and the difficulty of the items as locations on a continuous latent variable. (wikipedia.org)
  • authors
  • Mathematically, the authors identify the "interport model" as an extension of the conventional transshipment problem in a hub-and-spokes configuration with the interport treated as a novel kind of hub. (igi-global.com)