Conditional logistic regression is an extension of logistic regression that allows one to account for stratification and matching. Its main field of application is observational studies and in …

Can we test change in outcome (H0: Pr(D=1/pre trt)=Pr(D=1/post trt)) using a 2 test based on this table? NO, because the test based on this table assumes the rows are INDEPENDENT …

An introduction to regression methods using R with examples from public health datasets and accessible to students without a background in mathematical statistics.

SAS Proc Logistic will give us the conditional logistic regression estimate of the odds ratio, and an exact 95% confidence interval for the odds ratio using the conditional likelihood.

To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case–control data.

This report is the conditional logistic regression analog of the analysis of variance table. It displays the results of chi-square tests used to test whether each of the individual terms in the …

Learn what is Conditional Logistic Regression and its applications in data analysis and statistics.

Performing a logistic regression analysis on this would result in needing dummy variables for each pair! Doing so results in too many fixed effects to estimate with respect to the sample size and …

Some binomial sampling schemes in Biostatistics or Biology may result in what is called matched case-control data, which require a conditional logistic regression model.

Estimates a logistic regression model by maximizing the conditional likelihood. The conditional likelihood calculations are exact, and scale efficiently to strata with large numbers of cases.