In many medical comparative studies (e.g., comparison of two treatments in an otolaryngological study), subjects may produce either bilateral (e.g., responses from a pair of ears) or unilateral (response from only one ear) data. For bilateral cases, it is meaningful to assume that the information between the two ears from the same subject are generally highly correlated. In this article, we would like to test the equality of the successful cure rates between two treatments with the presence of combined unilateral and bilateral data. Based on the dependence and independence models, we study ten test statistics which utilize both the unilateral and bilateral data. The performance of these statistics will be evaluated with respect to their empirical Type I error rates and powers under different configurations. We find that both Rosner's and Wald-type statistics based on the dependence model and constrained maximum likelihood estimates (under the null hypothesis) perform satisfactorily for small to large samples and are hence recommended. We illustrate our methodologies with a real data set from an otolaryngology study.
|Original language||English (US)|
|Number of pages||15|
|Journal||Communications in Statistics: Simulation and Computation|
|State||Published - Sep 1 2008|
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Modeling and Simulation