An application of the LFP survival model to smoking cessation data

We use a limited failure population (LFP) model based on the Weibull distribution to model the times from initial abstinence to return to smoking for subjects enrolled in programmes to help them stop smoking. The model contains a third parameter that corresponds to the proportion of subjects who permanently abstain from smoking. The data are subject to both right and interval censoring. Furthermore, subjects receive treatment in groups, and individuals in the same group may provide correlated outcomes. Use of a maximum likelihood estimation procedure which assumes independent outcomes provides reasonable parameter estimates, but the corresponding standard errors tend to be too small, which results in tests with inflated type I error levels and confidence intervals that tend to be too narrow. We use a bootstrap procedure to obtain more reasonable values for the standard errors and to construct confidence intervals that more nearly achieve the stated coverage probabilities.