- Summary
- Contents
- Subject index
A must-have reference resource for qualitative management researchers, this dictionary contains over 90 entries covering the fundamentals of qualitative methodologies; covering both analysis and implementation. Each entry gives an introduction to the topic, lists the key relevant features, gives a worked example, a concise summary and a selection of further reading suggestions. It is suitable for researchers and academics who need a handy and quick point of reference.
Multinomial Logistic Regression
Multinomial Logistic Regression
Introduction
The generalized linear modelling technique of multinomial logistic regression can be used to model unordered categorical response variables. This model can be understood as a simple extension of logistic regression that allows each category of an unordered response variable to be compared to an arbitrary reference category providing a number of logit regression models. A binary logistic regression model compares one dichotomy (e.g. passed–failed, died–survived, etc.), whereas the multinomial logistic regression model compares a number of dichotomies. This procedure outputs a number of logistic regression models that make specific comparisons of the response categories. When there are j categories of the response variable, the model consists of j − 1 logit equations which are fit simultaneously. Multinomial logistic regression is a ...
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