Nonparametric methods for analyzing incomplete nondecreasing repeated measurements.

In comparing the effectiveness of two treatments, suppose that nondecreasing repeated measurements of the same characteristic are scheduled to be taken over a common set of time points for each study subject. A class of univariate one-sided global asymptotically distribution-free tests is proposed to test the equality of the two treatments. The test procedures allow different patterns of missing observations in the two groups to be compared, although the missing data mechanism is required to be independent of the observations in each treatment group. Test-based point and interval estimators of the global treatment difference are given. Multiple inference procedures are also provided to examine the time trend of treatment differences over the entire study. The proposed methods are illustrated by an example from a bladder cancer study.