Chapter 6

Logistic Regression for Ordered Categories

6.1   Introduction

6.2   Cumulative Logit Model: Example

6.3   Cumulative Logit Model: Explanation

6.4   Cumulative Logit Model: Practical Considerations

6.5   Cumulative Logit Model: Contingency Tables

6.6   Adjacent Categories Model

6.7   Continuation Ratio Model

 

6.1 Introduction

In the previous chapter we studied the multinomial logit model for dependent variables with three or more unordered categories. When the categories are ordered, it is sometimes useful to ignore the ordering and estimate the unordered multinomial model. However, there are two reasons for preferring models that take the ordering into account:

▪ They are simpler, and therefore easier to interpret.

▪ Hypothesis tests ...

Get Logistic Regression Using SAS, 2nd Edition now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.