A type of restricted maximum likelihood estimator of variance components in generalised linear mixed models
| Autor: | Jiangang (Jason) Liao, Stuart R. Lipsitz |
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| Rok vydání: | 2002 |
| Předmět: |
Statistics and Probability
Bayes estimator Mean squared error Restricted maximum likelihood Estimation theory Applied Mathematics General Mathematics Agricultural and Biological Sciences (miscellaneous) Minimum-variance unbiased estimator Efficient estimator Bias of an estimator Statistics Consistent estimator Statistics Probability and Uncertainty General Agricultural and Biological Sciences Mathematics |
| Zdroj: | Biometrika. 89:401-409 |
| ISSN: | 1464-3510 0006-3444 |
| DOI: | 10.1093/biomet/89.2.401 |
| Popis: | SUMMARY The maximum likelihood estimator of the variance components in a linear model can be biased downwards. Restricted maximum likelihood (REML) corrects this problem by using the likelihood of a set of residual contrasts and is generally considered superior. However, this original restricted maximum likelihood definition does not directly extend beyond linear models. We propose a REML-type estimator for generalised linear mixed models by correcting the bias in the profile score function of the variance components. The proposed estimator has the same consistency properties as the maximum likelihood estimator if the number of parameters in the mean and variance components models remains fixed. However, the estimator of the variance components has a smaller finite sample bias. A simulation study with a logistic mixed model shows that the proposed estimator is effective in correcting the downward bias in the maximum likelihood estimator. |
| Databáze: | OpenAIRE |
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