Imrey, Koch, Stokes and collaborators (1981) have reviewed the literature of log linear and logistic categorical data modelling, and presented a matrix formulation of log linear models parallel to the ...

A log-logistic regression model is described in which the hazard functions for separate samples converge with time. This also provides a linear model for the log odds on survival by any chosen time.

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

After linkage with inpatient discharge data, multistate and log-linear Poisson regression models were used to calculate hospitalization rates and to model rehospitalization in the year after diagnosis ...

As the title “Practical Regression” suggests, these notes are a guide to performing regression in practice. This note explains how to choose between log and linear specification. The note emphasizes ...

The resulting incidence rates for type 1 diabetes were analyzed with the use of Poisson regression (log-linear regression on the incidence rates with the use of the logarithms of the follow-up ...