 Robust variance estimation for rate ratio parameter estimates from individually matched case-control dataAnny Hui Xiang Biometrika, 2003, vol. 90, issue 3, 741-746 Abstract: The asymptotic variance and robust variance estimators of rate ratios estimated using conditional logistic regression from individually-matched case-control data are derived when the presumed proportional hazards model is misspecified. The robust variance estimators are easily computed using Schoenfeld residuals generated from standard partial likelihood estimation software for failure time data. Simulation studies indicate that the robust variance estimators perform well for typical sizes and that the 'rare disease' version should be adequate for all practical purposes. It was also found that model misspecification must be quite extreme before the model-based, i.e. inverse information, variance is significantly biased and that the robust variance estimators are somewhat more variable than the model-based. We conclude that the model-based variance estimator can be used when model misspecification is not severe. The robust estimator should be used when the presumed model clearly fits the data poorly. Copyright Biometrika Trust 2003, Oxford University Press. Date: 2003 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oup:biomet:v:90:y:2003:i:3:p:741-746 Ordering information: This journal article can be ordered from Access Statistics for this article Biometrika is currently edited by Paul Fearnhead More articles in Biometrika from Biometrika Trust Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. |
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