Résumé :
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[BDSP. Notice produite par INIST F94R0xBl. Diffusion soumise à autorisation]. A misclassification model is presented for the assessment of bias in rate ratios estimated by person-time analyses of automated medical care databases. The model allows for misclassification of events and person-time and applies to both differential and nondifferential errors. The focus is on medical care exposures that occur at discrete points in time (e.g., vaccinations) and on adverse events that are closely associated in time. Bias corrections for rate ratios and binomial tests of equality of event rates during exposed and unexposed person-time are developed and illustrated. For nondifferential under-or over-ascertainment of events, the observed rate ratio (r) is unbiased at the null hypothesis (true rate ratio R=1), negatively biased when R>1, and positively biased when R
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