Summary In practice, when analyzing data from a capture–recapture experiment it is tempting to apply modern advanced statistical methods to the observed capture histories. However, unless the analysis takes into account that the data have only been collected from individuals who have been captured at least once, the results may be biased. Without the development of new software packages, methods such as generalized additive models, generalized linear mixed models, and simulation–extrapolation cannot be readily implemented. In contrast, the partial likelihood approach allows the analysis of a capture–recapture experiment to be conducted using commonly available software. Here we examine the efficiency of this approach and apply it to several data sets.