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Correcting for selection bias in estimation of within‐individual variance
Author(s) -
Wilson P. David
Publication year - 1988
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.4780070307
Subject(s) - estimator , bivariate analysis , variance (accounting) , statistics , mathematics , normality , bias of an estimator , selection (genetic algorithm) , variable (mathematics) , minimum variance unbiased estimator , cutoff , independence (probability theory) , econometrics , computer science , mathematical analysis , physics , accounting , quantum mechanics , artificial intelligence , business
Consider a variable whose expected value distributes among individuals in a population, and which also has an important component of within‐individual variance. In a screening study that involves repeated observations only for those individuals whose initial observation exceeds an arbitrary cutoff point, the usual estimator of within‐individual variance is biased. Assuming normality and independence, this note gives the derivation of the expected value of the estimator and uses it to obtain an unbiased estimator. The results generalize to the bivariate case that involves selection on only one variable of the pair. A companion paper 1 provides an example with use of blood pressure.