Comparing Neural Network and Ordinal Logistic Regression to Analyze Attitude Responses

Ordinal logistic regression.

©FSRH J Fam Plann Reprod Health Care 2008: 34(3) What is it? When a response variable has only two possible values (e.g. recurrence/not), binary logistic regression is commonly used to test or model the association between that response and a number of potential explanatory variables, with each association estimated in terms of an odds ratio (OR). Multinomial logistic regression is an extension...

Multinomial and ordinal logistic regression using PROC LOGISTIC

Logistic regression may be useful when we are trying to model a categorical dependent variable (DV) as a function of one or more independent variables. This paper reviews the case when the DV has more than two levels, either ordered or not, gives and explains SAS R © code for these methods, and illustrates them with examples.

Comparing Neural Network, Logistic Regression, and Discriminant Analysis for Knowledge Representation and Classification Explanation

Many research studies have proved neural networks as a viable alternative to statistical models for classification tasks. However, compared with statistical models, neural networks have had the drawback of being unable to explain its classification logic until the development of rule extraction algorithms from trained neural networks. This research attempts to compare the results of the rule ex...

[Ordinal logistic regression in epidemiological studies].

Ordinal logistic regression models have been developed for analysis of epidemiological studies. However, the adequacy of such models for adjustment has so far received little attention. In this article, we reviewed the most important ordinal regression models and common approaches used to verify goodness-of-fit, using R or Stata programs. We performed formal and graphical analyses to compare or...

Logistic Regression for Multivariate Longitudinal Ordinal Data