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 ...

This is a preview. Log in through your library . Abstract A random-effects ordinal regression model is proposed for analysis of clustered or longitudinal ordinal response data. This model is developed ...

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 ...

The sampled correction term is imputed in the Markov chain pertaining to the regression parameters. The model was fitted to the oral health data of the Signal-Tandmobiel® study. A WinBUGS program was ...

The LOGISTIC and PROBIT procedures treat all response variables with more than two levels as ordinal responses and fit the proportional odds model. The GENMOD procedure fits this model with a link ...

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 ...