Abstract
Breslow (1981, Biometrika 68, 73-84) has shown that the Mantel-Haenszel odds ratio is a consistent estimator of a common odds ratio in sparse stratifications. For cohort studies, however, estimation of a common risk ratio or risk difference can be of greater interest. Under a binomial sparse-data model, the Mantel-Haenszel risk ratio and risk difference estimators are consistent in sparse stratifications, while the maximum likelihood and weighted least squares estimators are biased. Under Poisson sparse-data models, the Mantel-Haenszel and maximum likelihood rate ratio estimators have equal asymptotic variances under the null hypothesis and are consistent, while the weighted least squares estimators are again biased; similarly, of the common rate difference estimators the weighted least squares estimators are biased, while the estimator employing "Mantel-Haenszel" weights is consistent in sparse data. Variance estimators that are consistent in both sparse data and large strata can be derived for all the Mantel-Haenszel estimators.
Keywords
EstimatorStatisticsMathematicsPoisson distributionM-estimatorEconometrics
MeSH Terms
Analysis of VarianceFollow-Up StudiesHumansProbabilityResearch DesignRisk
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Publication Info
- Year
- 1985
- Type
- article
- Volume
- 41
- Issue
- 1
- Pages
- 55-55
- Citations
- 790
- Access
- Closed
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Cite This
Sander Greenland,
James M. Robins
(1985).
Estimation of a Common Effect Parameter from Sparse Follow-Up Data.
Biometrics
, 41
(1)
, 55-55.
https://doi.org/10.2307/2530643
Identifiers
- DOI
- 10.2307/2530643
- PMID
- 4005387