Asymptotic Sample Size for Common Test of Relative Risk Ratios in Stratified Bilateral Data

Abstract

In medical clinical studies, various tests usually relate to the sample size. This paper proposes several methods to calculate sample sizes for a common test of relative risk ratios in stratified bilateral data. Under the prespecified significant level and power, we derive some explicit formulae and an algorithm of the sample size. The sample sizes of the stratified intra-class model are obtained from the likelihood ratio, score, and Wald-type tests. Under pooled data, we calculate sample size based on the Wald-type test and its log-transformation form. Numerical simulations show that the proposed sample sizes have empirical power close to the prespecified value for given significance levels. The sample sizes from the iterative method are more stable and effective.