Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
416880 | Computational Statistics & Data Analysis | 2006 | 18 Pages |
Incomplete correlated 2×22×2 tables are common in infectious disease studies and 2-step treatment studies in which one of the comparative measures of interest is the rate/risk difference (RD) between the marginal probability and the conditional probability. In this paper, we consider an interval hypothesis test about the RD in an incomplete correlated 2×22×2 table. We propose two asymptotic test statistics, a Wald-type (sample-based) test statistic and a constrained maximum likelihood estimation (CMLE-based) test statistic to test the interval hypothesis. The sample sizes based on the above two tests for two types of analyses: hypothesis testing and confidence interval estimation are proposed. The true type I error rates and powers of the two tests are computed by enumerating the exact probabilities in the rejection region. Our empirical results show that the CMLE-based test performs better than the sample-based test in the sense that its significance level is much closer to the prespecified nominal level, its confidence interval estimator generally possesses shorter confidence interval width with coverage probability close to the prespecified confidence level. Two real examples are used to illustrate the proposed methods.