Exact inference on contrasts in means of intraclass correlation models with missing responses

Intraclass correlation models with missing data at random are considered. With a properly reduced model, a general method, which allows repeated observations with missing data in a non-monotone pattern, is proposed to construct exact test statistics and simultaneous confidence intervals for linear contrasts in the means. Simulation results are given to compare exact and asymptotic simultaneous confidence intervals. A real example is provided for the illustration of the proposed method.