**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 States**

**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.

**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.

**Japan**

**Health 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.

**Italy**

**Food 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.

**Brazil**

**Educational 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.

###### Rasch Measurement Program Comparisons on the Linear **Logistic** **Test** **Model** | RTI

###### 22954 - The PROC **LOGISTIC** proportional odds **test** and fitting a partial proportional odds **model**

###### A **Logistic** **Model** for Time-Limit **Tests** | Springer for Research & Development

###### ERIC - Locally Dependent Linear **Logistic** **Test** **Model** with Person Covariates, Applied Psychological Measurement, 2009

###### "Assessing Poisson and **Logistic** Regression **Models** Using Smooth **Tests**" by Paul Rippon and John Rayner

###### A COMPARISON OF GOODNESS‐OF‐FIT **TESTS** FOR THE **LOGISTIC** REGRESSION **MODEL**, Statistics in Medicine | 10.1002/(SICI)1097-0258...

###### Non-Inferiority **Test** in Multple **Logistic** **Model** | Statistics Help @ Talk Stats Forum

###### Interpretation of different **logistic** regression **models** to **test** hypotheses - Cross Validated

###### Use of a combination of routine hematologic and biochemical **test** results in a **logistic** regression **model** as a diagnostic aid for...

###### Why does sign of coefficient of categorical variable changes in **logistic** regression when running a **model** on **test** sample - Cross...

###### Assignment 4 RMIP: **Test** a **Logistic** Regression **Model** | PetroSai

###### A Study on V50 Calculation in Bulletproof **Test** using **Logistic** Regression **Model**

###### CRAN - Package generalhoslem

###### generalhoslem: Goodness of Fit **Tests** for **Logistic** Regression **Models** version 1.3.2 from CRAN

###### Brunel University Research Archive **Test**: Properties of estimators of parameters in **logistic** regression **models**

###### New **Logistics** **Model** Improves Forecast Accuracy of Retail and Packaged-Goods Orders

###### SAP **Model** Company for **Logistics** Execution

###### 6d8e3a 845ee1af6bad4749b22eb1ed8fca3228 | **Logistic** Regression | **Test** Set

###### CYP2B6 and bupropion's smoking-cessation pharmacology: the role of hydroxybupropion

###### Biomarkers of rapid chronic kidney disease progression in type 2 diabetes

###### Study on Probability Estimation of Haze in Beijing Based **Logistic** Regression **Model**

###### Risk Associated With the Metabolic Syndrome Versus the Sum of Its Individual Components | Diabetes Care

###### Analysis of Variance, Design, and Regression: Linear **Modeling** for Unba

###### Example 61.4 **Logistic** Regression **Model** with Jeffreys' Prior :: SAS/STAT(R) 13.2 User's Guide

###### A review of **test** for trend : score **tests** and likelihood ratio **tests** using linear **logistic** **model** and log-linear **model** with...

###### Using mixed effects **logistic** regression **models** for complex survey data on malaria rapid diagnostic **test** results | Malaria...

**Logistic** Prediction **Model** of Robert et al for Probability of Coronary Artery Disease in a Woman Undergoing Exercise **Testing** |...

ProbabilityEffects logistic regression modelsCoefficientsRaschStepwiseEstimateEstimationPROC GENMODAssumptionsProbabilitiesPracticeMethodsItem responEfficacyNonlinearHosmer-LemeshowProbitOptimizeLikelihood ratio testsRegularizationAssessmentWilcoxonInterpretationStatistically significantStatistical modelAnovaPrediction ModelHazardIncorporateParametricCovariatesProportional hazards modelWaldPatientsEstimatorsOptimizationDifferentialIndicatorPsychological

###### Probability11

- The DESCENDING response variable option allows you to model the probability of the higher response levels NOTE . (sas.com)
- Zhu, Y. , Zhang, T. and Chen, C. (2017) Study on Probability Estimation of Haze in Beijing Based Logistic Regression Model. (scirp.org)
- First, the LR models were established to calculate the probability of being bad credit for each customer, in order to discriminate that this customer has good credit or bad credit. (scirp.org)
- Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. (wiley.com)
- The growth of B. cereus was evaluated by optical density (OD) measurements in culture media for various pHs (5.5 ∼ 7.0) and salt concentrations (0.5 ∼ 2.0%) at static temperatures (10 ∼ 20°C). The probability of the end of λ was modeled using dichotomous judgments obtained at each OD measurement point concerning whether a significant increase had been observed. (asm.org)
- The mortality probability of trees is modeled as a function of recent growth and tree size. (frontiersin.org)
- In this study, we focus on such early-warning signals of tree death and we model the mortality probability as a function of recent growth and tree height. (frontiersin.org)
- The final model was transformed into a clinical prediction model that allows practitioners to calculate the probability of a child having LM. (aappublications.org)
- EDF Energy has created a dedicated analytics function to focus on key areas including customer segmentation, churn assessment, probability modelling and product placement modelling. (sas.com)
- Review of introductory concepts in statistics and probability including hypothesis testing, estimation and confidence intervals for means and proportions. (sfu.ca)
- Review of basic concepts of probability with applications including diagnostic testing, sensitivity and specificity, the relative risk and the odds ratio. (sfu.ca)

###### Effects logistic regression models2

- When analyzing common tumors, within-litter correlations can be included into the mixed effects logistic regression models used to test for dose-effects. (jyi.org)
- The objective of this study is to determine the conditions under which mixed effects logistic regression models fail to converge using SAS procedures with litter correlations. (jyi.org)

###### Coefficients4

- Properties of various types of estimators of the regression coefficients in linear logistic regression models are considered. (brunel.ac.uk)
- Interpretation of model coefficients as differences in means or odds ratios. (bristol.ac.uk)
- Significance testing for the logistic coefficients using Wald test and likelihood ratio show that five risk factors were significant. (statjournals.net)
- Correlation and simple linear regression: Regression concepts, estimation and testing for regression coefficients, evaluation of the model. (sfu.ca)

###### Rasch13

- Rasch models: Foundations, recent developments and applications (pp. 131-155). (springer.com)
- Testing the Rasch model. (springer.com)
- Rasch models: Their foundations, recent developments and applications (pp. 69-95). (springer.com)
- A Rasch model for partial credit scoring. (springer.com)
- The publisher of the Degrees of Reading Power test of reading comprehension (DRP) calibrate their test using an item response model called the Rasch or one-parameter logistic model. (vt.edu)
- The relationship between the use of the Rasch model in calibration of the DRP and the use of the DRP as a component of the Virginia Literacy Passport Testing Program (LPT) is addressed. (vt.edu)
- The question that arises is whether the Rasch model is the appropriate model to use to calibrate the DRP in this high-stakes setting. (vt.edu)
- The majority of research that has been reported by the publisher of the DRP to assess the adequacy of the Rasch model have not included direct checks on model assumptions, model features or model predictions. (vt.edu)
- This study will assess the adequacy of fitting DRP test data to the Rasch model through direct examination of the assumptions, features and predictions of the IRT model. (vt.edu)
- This is accomplished by comparing the Rasch model to the less restrictive two- and three-parameter logistic models. (vt.edu)
- Andrich, D. (2004) Controversy and the Rasch model: A characteristic of incompatible paradigms? (rasch.org)
- His main research work focuses on fundamental research of assessment processes and on application and advancement of Item response theory models (Rasch model). (wikipedia.org)
- Psychological Test Calibration using the Rasch Model - Some Critical Suggestions on Traditional Approaches. (wikipedia.org)

###### Stepwise1

- This video reviews the variables to be used in stepwise selection logistic regression modeling in this demonstration. (lynda.com)

###### Estimate12

- The direction of an effect may be of particular interest to the business, but that doesn't imply that a change in the direction of its estimate between training & test is a stronger indication of problems with the model selection & fitting process than any other change of similar magnitude. (stackexchange.com)
- See here, I put the estimate for diabetes and next to it … I put the confidence interval and since we just ran … this model in our 600 code we know that diabflag … is statistically significant, here are the numbers. (lynda.com)
- Dose-response meta-analyses were performed using a random-effects model to estimate summary relative risk (RR) and 95% confidence interval (CI) for each cancer type. (cdc.gov)
- In this paper, the personal credit assessment models were established by combining back-propagation neural network (BPNN) and logistic regression, to estimate the customers' behaviors for a communication corporation. (scirp.org)
- Estimate posterior class probabilities for a test set, and determine the quality of the model by plotting a receiver operating characteristic (ROC) curve. (mathworks.com)
- 18 000 income per year) and Primary Care Service Area Socioeconomic Index (from 0 to 100 categorized in quartiles).We used mixed-effects logistic and survival models to estimate odds ratios and hazard ratios for the short- (30 days) and the long-term (3 years) all-cause case fatality rates by individuals' socioeconomic status groups. (medscape.com)
- If the test wanted to estimate how frequently the circuits needed to be replaced, then the category of low failure would also be applicable. (wikipedia.org)
- When the appropriate model is not known in advance, or there exist multiple accepted models, the test must estimate what model fits best based on the context of the test and results from testing. (wikipedia.org)
- A possible pre-experiment approach to minimize this is to estimate what data you expect from testing, fit a model to the data, and determine if one would be able to make reliable conclusions if everything went as expected. (wikipedia.org)
- We use estat icc to estimate the intraclass correlations for this model. (stata.com)
- The model can be used to estimate when the reliability goal of 99% will be achieved if testing and improvements continue. (weibull.com)
- The model was used to estimate the reliability throughout the test and estimate additional trials needed to demonstrate a certain reliability goal. (weibull.com)

###### Estimation3

- In this study, we proposed a V 50 estimation method using logistic regression analysis. (jksqm.org)
- Recent Results on Quantlie Estimation Methods in Simulation Model. (indigo.ca)
- Position entails statistical estimation and testing for adverse impact in employer hiring, compensation, promotion and termination processes. (simplyhired.com)

###### PROC GENMOD1

- PROC GENMOD fits the same proportional odds model, but it does not provide a proportional odds test. (sas.com)

###### Assumptions1

###### Probabilities2

- Kernel classification models return posterior probabilities for logistic regression learners only. (mathworks.com)
- Predict the posterior class probabilities for the test set. (mathworks.com)

###### Practice2

- For the final week in the 'Regression Modeling in Practice' course, I will be testing a logistic regression model using the Marscrater dataset to examine my research question. (petrosaiservices.com)
- Posted in Regression Modeling in Practice Course . (petrosaiservices.com)

###### Methods2

- Personal credit assessment requires establishing calibration models with statistic methods. (scirp.org)
- Revision of basic methods in a statistical modelling framework. (bristol.ac.uk)

###### Item respon2

###### Efficacy1

- In this model, pre-treatment PD20FEV1-LTD4 represented anticipated efficacy. (clinicaltrials.gov)

###### Nonlinear1

- Identifiability of nonlinear logistic test models. (springer.com)

###### Hosmer-Lemeshow1

- The Hosmer-Lemeshow test was performed and the area under the receiver operating characteristic curve was calculated. (aappublications.org)

###### Probit1

###### Optimize1

- This study aims to optimize causative factors using logistic regression (LR) and an artificial neural network (ANN) to produce a LSM. (springer.com)

###### Likelihood ratio tests1

- Comparing models with Wald tests and likelihood ratio tests. (bristol.ac.uk)

###### Regularization1

- Classification models through an application of the KNN algorithm Logistic Regression -Learn to apply regularization and optimization when evaluating model fit. (eventbrite.com)

###### Assessment7

- Derr (2013) also discusses the testing and assessment of the proportional odds assumption. (sas.com)
- Instead, they have relied almost exclusively on statistical tests in assessment of model fit. (vt.edu)
- Verb fluency (VF) is the less commonly used fluency test, despite several studies suggesting its potential as a neuropsychological assessment tool. (nih.gov)
- It is an encouraging preliminary model towards a systematic introduction of FSLR-ANN model for optimization causative factors in landslide susceptibility assessment in the mountainous area of Ujung Loe Watershed. (springer.com)
- From this time on, he is head of the division of psychological assessment and applied psychomterics, which includes a Center of Testing and Consulting. (wikipedia.org)
- since 2003 Editor in Chief of Psychological Test and Assessment Modeling since 2005 Board member of Journal of Individual Differences since 2007 Board member of International Journal of Selection and Assessment 2007: Alfred-Binet-Award of the German Society of Psychology. (wikipedia.org)
- The technique of objective personality-tests sensu R.B. Cattell nowadays: The Viennese pool of computerized tests aimed at experiment-based assessment of behavior. (wikipedia.org)

###### Wilcoxon1

- Differences between groups were assessed by χ 2 , Fisher's exact, and Wilcoxon rank sum tests. (springer.com)

###### Interpretation1

- The mono-method-based models are not capable to simultaneously hold the robustness, interpretation and prediction accuracy of the models. (scirp.org)

###### Statistically significant2

- Exposure from more than 10 tanning sessions is most strongly associated and there was no statistically significant difference in this association before and after 2000, suggesting that newer tanning technology is not safer than older models. (cdc.gov)
- Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. (mdpi.com)

###### Statistical model3

- The statistical model we used provides a better understanding of orders in a supply chain and can improve short-term forecasting," said Matt Waller, professor of marketing and logistics in the Sam M. Walton College of Business. (phys.org)
- To create a statistical model to predict LM versus AM in children based on history, physical, and laboratory findings during the initial presentation of meningitis. (aappublications.org)
- A total of 175 children with meningitis were included in the final statistical model. (aappublications.org)

###### Anova2

- Special cases of the regression model, ANOVA and ANCOVA will be covered as well. (coursera.org)
- We contrasted the headache end-points using anova with post-test and Kruskal-Wallis with post-test. (wiley.com)

###### Prediction Model1

- No large studies have compared patients with LM to all patients presenting with AM and attempted to define a clinical prediction model. (aappublications.org)

###### Hazard1

- We calculated absolute rate of fracture and hazard ratios (HRs) using Cox regression models. (cmaj.ca)

###### Incorporate2

- Incorporate a broad range of modelling techniques including logistic regression. (sas.com)
- Some models must be altered to incorporate litter effect, including the dose response model (Khera et al. (jyi.org)

###### Parametric1

- Then it moves on to models for continuous time, first addressing parametric models and then the Cox proportional hazards model. (stata.com)

###### Covariates2

- We propose a class of so-called sum of powered score (SPU) tests, each of which is based on the score vector from a general regression model and hence can deal with different types of traits and adjust for covariates, e.g. , principal components accounting for population stratification. (genetics.org)
- In the logistic regression model, BMI did not account for changes in disability, headache frequency, or in the number of days with severe headache per month, after adjusting for covariates. (wiley.com)

###### Proportional hazards model1

- Cox Proportional Hazards Model. (york.ac.uk)

###### Wald1

- The likelihood ratio, Wald and Lagrange multiplier test: An expository note. (springer.com)

###### Patients4

- Severe leptospirosis in model has its limits in the context of hospitalized patients, Guadeloupe. (cdc.gov)
- tial risk factors among these patients tion of serovar and species can only be Author affi liation: Central University Hospi- by applying a multivariable logistic re- accomplished by isolating Leptospira tal, Pointe-à-Pitre, Gaudeloupe, France gression model. (cdc.gov)
- Logistic-regression analysis included 27 patients with LM and 148 patients classified as having AM. Duration of headache, cranial neuritis, and percent CSF mononuclear cells independently predicted LM. (aappublications.org)
- The logistic regression model is used to determine the social-demographic risk factors which affect the second cancer occurrence for 200 patients who were initially treated for first primary cancer stage I and were cancer free for at least 1 year after first primary cancer treatment. (statjournals.net)

###### Estimators1

- It was also found that both estimators provide exactly regression weight, but the statistical inferential tests are slightly different. (inderscience.com)

###### Optimization3

- One director attended a CLM (Council of Logistics Management) conference and learned that savings in logistics operating costs are typically in the 10 percent to 15 percent range from conducting a logistics network optimization project. (mhlnews.com)
- Then, a BPNN model with one hidden layer was used to generate a new comprehensive variable for model optimization by tuning and selecting the number of hidden nodes. (scirp.org)
- Overall, it was determined that when the dependent variable has a rare occurrence, optimization of the mixed model fitting cannot be completed and the tests for dose effects cannot be conducted. (jyi.org)

###### Differential4

- This article evaluates the differential prediction of the three and four-factor models of the PCL:YV for male (n=201) and female (n=55) juvenile offenders using a prospective four and one-half year follow-up (M=3 years) study. (bepress.com)
- The VF test may be a useful tool for the differential diagnosis of cognitive failure in the elderly. (nih.gov)
- The developed λ model was subsequently combined with a logistic differential equation to simulate bacterial numbers over time. (asm.org)
- Furthermore, the λ model, in combination with a logistic differential equation, enabled a simulation of the population of B. cereus in various foods over time at static and/or fluctuating temperatures with high accuracy. (asm.org)

###### Indicator1

- Objective４To investigate whether leukotriene D4 bronchial provocation test (LTD4-BPT) could be an indicator of actual therapeutic outcome of LTRA. (clinicaltrials.gov)

###### Psychological3

- Einfurung in die Theorie psychologischer Tests: Grundlagen und Anwendungen [Introduction to the theory of psychological tests: Foundations and applications]. (springer.com)
- Einfiihrung in die Theorie psychologischer Tests [Introduction to the Theory of Psychological Tests]. (springer.com)
- These models provide a means for rule-based item generation in educational and psychological testing based upon cognitive theories. (uni-magdeburg.de)