Spiess, Martin (1998) A mixed approach for the estimation of probit models with correlated responses: Some finite sample results. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 61 (1-2). pp. 39-59. ISSN 0094-9655
Full text not available from this repository.Abstract
In the present paper a mixed approach for the simultaneous estimation of regression and correlation structure parameters in probit models with correlated responses proposed by Spiess and Hamerle (1996a) is compared to an approach proposed by Qu, Williams, Beck and Medendorp (1992) and Qu, Piedmonte and Williams (1994) via a Monte Carlo experiment. Whereas in the former approach generalized estimating equations for the estimation of regression parameters and pseudo-score equations for the estimation of association parameters are used, in the latter approach both sets of parameters are estimated using generalized estimating equations. As a 'reference' estimator for an equicorrelation model, the maximum likelihood (ML) estimator of a random effects probit model is calculated. The results show that the mixed approach leads to the most efficient non-ML estimators for regression and correlation structure parameters if individual covariance matrices are used. Furthermore, for the equicorrelation model, the loss of efficiency is small relative to the ML estimator.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | LATENT VARIABLE MODELS; BINARY REGRESSION; generalized estimating equations; pseudo-score equations; correlated categorical responses; panel data; simulation study |
| Subjects: | 300 Social sciences > 330 Economics |
| Divisions: | Business, Economics and Information Systems > Institut für Betriebswirtschaftslehre > Entpflichtete oder im Ruhestand befindliche Professoren > Lehrstuhl für Statistik (Prof. Dr. Alfred Hamerle) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 28 Feb 2023 11:22 |
| Last Modified: | 28 Feb 2023 11:22 |
| URI: | https://pred.uni-regensburg.de/id/eprint/50248 |
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