Ordinal logistic regression models: application in quality of life studies

Ordinal logistic regression models: application in quality of life studies.

Quality of life has been increasingly emphasized in public health research in recent years. Typically, the results of quality of life are measured by means of ordinal scales. In these situations, specific statistical methods are necessary because procedures such as either dichotomization or misinformation on the distribution of the outcome variable may complicate the inferential process. Ordina...

[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...

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...

Marginalized models for longitudinal ordinal data with application to quality of life studies.

Random effects are often used in generalized linear models to explain the serial dependence for longitudinal categorical data. Marginalized random effects models (MREMs) for the analysis of longitudinal binary data have been proposed to permit likelihood-based estimation of marginal regression parameters. In this paper, we propose a model to extend the MREM to accommodate longitudinal ordinal d...

Logistic Regression for Multivariate Longitudinal Ordinal Data