Generalized linear random effects models with varying coefficients

Authors:
Gerhard Tutz;Göran Kauermann
Affiliations:
Institut für Statistik, Ludwig-Maximilians-Universität München, Ludwigstraße 33, D-80539 München, Germany;Department of Statistics, Mathematics Building University Gardens, University of Glasgow, University Gardens, Glasgow G12 8QW, Scotland UK
Venue:
Computational Statistics & Data Analysis
Year:
2003

Citing 2
Cited 1

Logistic regression with random coefficients

Computational Statistics & Data Analysis
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,

Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,

A bivariate frailty model for events with a permanent survivor fraction and non-monotonic hazards; with an application to age at first maternity

Computational Statistics & Data Analysis

Quantified Score

Hi-index	0.03

Visualization

Abstract

In longitudinal studies where subjects are measured repeatedly, the effect strength of covariates may vary with time. Additionally, observations taken at one individual have to be considered as dependent. These two aspects are accommodated in a model which allows for time-varying coefficients and include subject-specific effects to account for heterogeneity of subjects. The proposed estimation procedure is based on a localized version of the marginal likelihood approach in generalized linear models with random coefficients. The efficiency of the estimation procedure is demonstrated in a small simulation study and an application to real data is given.