Search results for "Dale model"
showing 2 items of 2 documents
A penalized approach for the bivariate ordered logistic model with applications to social and medical data
2018
Bivariate ordered logistic models (BOLMs) are appealing to jointly model the marginal distribution of two ordered responses and their association, given a set of covariates. When the number of categories of the responses increases, the number of global odds ratios to be estimated also increases, and estimation gets problematic. In this work we propose a non-parametric approach for the maximum likelihood (ML) estimation of a BOLM, wherein penalties to the differences between adjacent row and column effects are applied. Our proposal is then compared to the Goodman and Dale models. Some simulation results as well as analyses of two real data sets are presented and discussed.
The pblm package: semiparametric regression for bivariate categorical responses in R
2014
We present an R package to fit semiparametric regression models for two categorical responses. It works for both nominal and ordered responses and several types of logits can be specified. Proportional, non-proportional and partial proportional odds models can be fitted, with marginal and association parameters estimated in a parametric or semiparametric way, via penalized maximum likelihood estimation. An application to show the potential of the package is carried out on a data set of Italian university students.