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Bias in methods for deriving standardized morbidity ratio and attributable fraction estimates
Author(s) -
Greenland Sander
Publication year - 1984
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780030206
Subject(s) - estimator , fraction (chemistry) , statistics , attributable risk , variance (accounting) , econometrics , regression analysis , regression , mathematics , medicine , epidemiology , economics , chemistry , accounting , organic chemistry
This paper examines several methods for deriving standardized morbidity ratios (SMR) and attributable fraction (attributable risk percentage) estimates. We show that some of the proposed methods will, in general, produce biased estimators, although the low variance of certain estimators sometimes compensates for their bias. A few methods are based on statistical fallacies and should be avoided, especially the method of deriving the expected number of cases from a regression equation that does not include the exposure under study.