Impact of censoring types on the two-stage method for analyzing reliability experiments with random effects

Many reliability experiments are not completely randomized. Instead they involve subsamples, blocks, split-plot structures, etc. A common analysis often uses random effects to account for the impact of the experimental protocol. The two-stage method is an easy way for practitioners to incorporate random effects in the analysis. This article compares performance of the two-stage method under Type I, Type II censored, and uncensored data from a Weibull distribution. We evaluate the effects of censoring type, censoring rate, sample size, and shape parameter on the two-stage method. Then, we apply the two-stage method to a real experiment. Finally, we give practitioners some recommendations for designing and analyzing reliability experiments.