An Ordinal Regression Model Using Dealer Satisfaction Data

A mixed-effects regression model for longitudinal multivariate ordinal data.

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do no...

Variable length testing using the ordinal regression model.

Health questionnaires are often built up from sets of questions that are totaled to obtain a sum score. An important consideration in designing questionnaires is to minimize respondent burden. An increasingly popular method for efficient measurement is computerized adaptive testing; unfortunately, many health questionnaires do not meet the requirements for this method. In this paper, a new sequ...

Regression Models for Ordinal Data : AMachine Learning

In contrast to the standard machine learning tasks of classi cation and metric regression we investigate the problem of predicting variables of ordinal scale, a setting referred to as ordinal regression. The task of ordinal regression arises frequently in the social sciences and in information retrieval where human preferences play a major role. Also many multi{class problems are really problem...

Logistic Regression for Multivariate Longitudinal Ordinal Data

A composite logistic regression approach for ordinal panel data regression

We propose in this article a Composite Logistic Regression (CLR) approach for ordinal panel data regression. The new method transforms the original ordinal regression problem into a number of binary ones. Thereafter, the method of conditional logistic regression (Chamberlain, 1984; Wooldridge, 2001; Hsiao, 2003) can be directly applied. As a result, the new method allows the unobserved subject ...