Nam Jun-mo
Biostatistics Branch, Division of Cancer Epidemiology and Genetics, NCI, NIH, Department of Health & Human Services, Executive Plaza South, Room 8028, 6120 Executive Boulevard, MSC 7240, Rockville, Maryland 20892-7240, USA.
Biom J. 2006 Dec;48(6):966-77. doi: 10.1002/bimj.200510283.
We consider the statistical testing for non-inferiority of a new treatment compared with the standard one under matched-pair setting in a stratified study or in several trials. A non-inferiority test based on the efficient scores and a Mantel-Haenszel (M-H) like procedure with restricted maximum likelihood estimators (RMLEs) of nuisance parameters and their corresponding sample size formulae are presented. We evaluate the above tests and the M-H type Wald test in level and power. The stratified score test is conservative and provides the best power. The M-H like procedure with RMLEs gives an accurate level. However, the Wald test is anti-conservative and we suggest caution when it is used. The unstratified score test is not biased but it is less powerful than the stratified score test when base-line probabilities related to strata are not the same. This investigation shows that the stratified score test possesses optimum statistical properties in testing non-inferiority. A common difference between two proportions across strata is the basic assumption of the stratified tests, we present appropriate tests to validate the assumption and related remarks.
我们考虑在分层研究或多个试验的配对设置下，对新治疗方法与标准治疗方法进行非劣效性的统计检验。提出了一种基于有效得分的非劣效性检验，以及一种类似Mantel-Haenszel（M-H）程序的方法，该方法使用干扰参数的受限最大似然估计（RMLE）及其相应的样本量公式。我们在水平和功效方面评估上述检验以及M-H型Wald检验。分层得分检验是保守的，并且具有最佳功效。使用RMLE的类似M-H程序给出了准确的水平。然而，Wald检验是反保守的，我们建议在使用时谨慎。未分层得分检验无偏差，但当与各层相关的基线概率不同时，其功效低于分层得分检验。本研究表明，分层得分检验在非劣效性检验中具有最佳统计特性。各层中两个比例的共同差异是分层检验的基本假设，我们提出了适当的检验来验证该假设及相关说明。
