Introduction: We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) ...

A random-effects ordinal regression model is proposed for analysis of clustered or longitudinal ordinal response data. This model is developed for both the probit and logistic response functions.

The response variable y is ordinally scaled. A cumulative logit model is used to investigate the effects of the cheese additives on taste. The following SAS statements invoke PROC LOGISTIC to fit this ...

Logistic regression enables you to investigate the relationship between a categorical outcome and a set of explanatory variables. The outcome, or response, can be dichotomous (yes, no) or ordinal (low ...

Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...