Prospective and retrospective analyses under logistic regression models
In logistic case-control studies, Prentice and Pyke (Biometrika 66 (1979) 403-411) showed that valid point estimators of the odds-ratio parameters and their standard errors may be obtained by fitting the prospective logistic regression model to case-control data. Wang and Carroll (Biometrika 80 (1993) 237-241; J. Statist. Plann. Inference 43 (1995) 331-340) generalized Prentice and Pyke's (Biometrika 66 (1979) 403-411) results to robust logistic case-control studies. In this paper, we extend the results of Prentice and Pyke (Biometrika 66 (1979) 403-411) and Wang and Carroll (Biometrika 80 (1993) 237-241; J. Statist. Plann. Inference 43 (1995) 331-340) to a class of statistics and a class of unbiased estimating equations. We present some results on simulation and on the analysis of two real datasets.
Year of publication: |
2006
|
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Authors: | Zhang, Biao |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 97.2006, 1, p. 211-230
|
Publisher: |
Elsevier |
Keywords: | Case-control data Chi-squared Correlation coefficient Discriminant function statistic Fisher information matrix Fisher's z-transformation Maximum semiparametric likelihood Moment generating function Moore-Penrose generalized inverse Odds ratio Score equation Score statistic Unbiased estimating equation Wald statistic |
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