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Sample size determinations using logistic regression with pilot data
Author(s) -
Flack Virginia F.,
Eudey T. Lynn
Publication year - 1993
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.4780121107
Subject(s) - logistic regression , statistics , binomial regression , covariate , sample size determination , sample (material) , binomial (polynomial) , mathematics , negative binomial distribution , econometrics , binomial distribution , data set , computer science , chemistry , chromatography , poisson distribution
Suppose the goal of a projected study is to estimate accurately the value of a ‘prediction’ proportion p that is specific to a given set of covariates. Available pilot data show that (1) the covariates are influential in determining the value of p and (2) their relationship to p can be modelled as a logistic regression. A sample size justification for the projected study can be based on the logistic model; the resulting sample sizes not only are more reasonable than the usual binomial sample size values from a scientific standpoint (since they are based on a model that is more realistic), but also give smaller prediction standard errors than the binomial approach with the same sample size. In appropriate situations, the logistic‐based sample sizes could make the difference between a feasible proposal and an unfeasible, binomial‐based proposal. An example using pilot study data of dental radiographs demonstrates the methods.