Designing follow-up intervals

Abstract

When an examination is needed to determine if an event has occurred there will be a loss of efficiency in using the resulting interval-censored data instead of the exact event times. In designing follow-up intervals this loss for longer intervals needs to be weighed against extra visits required by shorter intervals. We obtain results to quantify this for the estimation of the median and mean survival and for covariates in parametric regression models with equally spaced examination times. Asymptotic information loss for the log-normal and Weibull distributions are similar when comparisons are made between corresponding members of the two families. For distributions with coefficients of variation of 50 per cent or more, a choice of interval from 0.25 to 0.7 times the median is recommended.