Logistic regression was used to develop a risk prediction model using the FIT result and screening data: age, sex and previous screening history.

We accommodate the longitudinal nature of the multiple outcomes with a unique extension of the nested random effects logistic model with an autoregressive structure to include drop-out and baseline ...

In this article, an exact conditional goodness-of-fit test for the logistic regression model with grouped binomial response data is proposed. Two efficient algorithms are presented for carrying out ...

The course covers contingency tables, Mantel-Haenszel test, measures of association and of agreement, logistic regression models, regression diagnostics, proportional odds, ordinal and polytomous ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

Multiple logistic regression models identified various combinations of these factors as predictive of MMR maintenance (Table 2 and for all the details, see the Data Supplement, Table S4).