On a Unified Generalized Quasi-likelihood Approach for Familial-Longitudinal Non-Stationary Count Data
In this paper, conditional on random family effects, we consider an auto-regression model for repeated count data and their corresponding time-dependent covariates, collected from the members of a large number of independent families. The count responses, in such a set up, unconditionally exhibit a non-stationary familial-longitudinal correlation structure. We then take this two-way correlation structure into account, and develop a generalized quasilikelihood (GQL) approach for the estimation of the regression effects and the familial correlation index parameter, whereas the longitudinal correlation parameter is estimated by using the well-known method of moments. The performance of the proposed estimation approach is examined through a simulation study. Some model mis-specification effects are also studied. The estimation methodology is illustrated by analysing real life healthcare utilization count data collected from 36 families of size four over a period of 4 years. Copyright (c) Board of the Foundation of the Scandinavian Journal of Statistics 2008.
Year of publication: |
2008
|
---|---|
Authors: | SUTRADHAR, BRAJENDRA C. ; JOWAHEER, VANDNA ; SNEDDON, GARY |
Published in: |
Scandinavian Journal of Statistics. - Danish Society for Theoretical Statistics, ISSN 0303-6898. - Vol. 35.2008, 4, p. 597-612
|
Publisher: |
Danish Society for Theoretical Statistics Finnish Statistical Society Norwegian Statistical Association Swedish Statistical Association |
Saved in:
freely available
Saved in favorites
Similar items by person
-
On semiparametric familial-longitudinal models
Sneddon, Gary, (2004)
-
On familial longitudinal Poisson mixed models with gamma random effects
Sutradhar, Brajendra C., (2003)
-
Hasan, M. Tariqul, (2012)
- More ...