Power series estimator for binary data

There are several commonly used measures of association between treatment and control event rates in the population, including odds ratios, relative risk and number needed to treat. Conventionally those parameters are estimated by the sample proportion estimators. In this paper, we show that the sam...

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Bibliographic Details
Published inJournal of statistical planning and inference Vol. 142; no. 2; pp. 579 - 588
Main Authors Wu, Chien-Hua, Wan, Shu-Mei
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier B.V 01.02.2012
Elsevier
Subjects
Exact sciences and technology
General topics
Mathematics
Multivariate analysis
Number needed to treat
Odds ratio
Power series estimator
Probability and statistics
Relative risk
Sciences and techniques of general use
Statistics
Odds ratio
Power series estimator
Number needed to treat
Relative risk
Statistical method
Association measure
Speed
Binary data
Statistical association
Statistical decision
Multivariate analysis
Power series
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Summary:There are several commonly used measures of association between treatment and control event rates in the population, including odds ratios, relative risk and number needed to treat. Conventionally those parameters are estimated by the sample proportion estimators. In this paper, we show that the sample proportional estimators tend to overestimate. Fortunately, those measurements are estimable by the power series estimators and they converge to UMVUE with a speed of convergency depending on big-O. For instance, it converges slowly for the number needed to treat if the difference between two sample proportions is close to zero.
ISSN:0378-3758
1873-1171
DOI:10.1016/j.jspi.2011.09.002