Chukiat ViwatwongkasemJirawan JitthavechDankmar BöhningVichit Lorchirachoonkulชูเกียรติ  วิวัฒน์วงศ์เกษมMahidol university. Faculty of Public Health. Department of Biostatistics2015-10-192017-07-122015-10-192017-07-122015-10-192012Open Journal of Statistics. Vol.2, (2012), 48-59https://repository.li.mahidol.ac.th/handle/123456789/2568The simple adjusted estimator of risk difference in each center is easy constructed by adding a value c on the number of successes and on the number of failures in each arm of the proportion estimator. Assessing a treatment effect in multi-center studies, we propose minimum MSE (mean square error) weights of an adjusted summary estimate of risk difference under the assumption of a constant of common risk difference over all centers. To evaluate the performance of the proposed weights, we compare not only in terms of estimation based on bias, variance, and MSE with two other conventional weights, such as the Cochran-Mantel-Haenszel weights and the inverse variance (weighted least square) weights, but also we compare the potential tests based on the type I error probability and the power of test in a variety of situations. The results illustrate that the proposed weights in terms of point estimation and hypothesis testing perform well and should be recommended to use as an alternative choice. Finally, two applications are illustrated for the practi- cal use.engMahidol universityMinimum MSE WeightsOptimal WeightsCochran-Mantel-Haenszel WeightsInverse Variance WeightsMulti-Center StudiesRisk DifferenceOpen Access articleArticle10.4236/ojs.2012.21006