SOME IMPLICATIONS OF AN ALTERNATIVE DEFINITION OF THE MULTIPLE COMPARISON PROBLEM
成果类型：
Article
署名作者：
HALPERIN, M; LAN, KKG; HAMDY, MI
署名单位：
George Washington University
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
发表日期：
1988
页码：
773778
关键词：
摘要：
An approach to multiple comparisons defines the error control objective as assuring with given probability that k or fewer out of N specific linear combinations of p means are significant when an overall null hypothesis is true, or that k or fewer confidence interval statements are incorrect. The case k=0 is basically the Scheffe (1953) method except for the consideration of a specified set of N linear combinations rather than all possible linear combinations. A theorectical result is obtained under normal theory and we assume an infinite number of linear combinations with normalized coefficients, that is the sum of squares is unity, uniformly distributed over the unit p-sphere. For a finite number N of specified linear combinations the problem is reformulated in a way which in principle would allow computation of the exact distributions required to provide critical values. In general, the computations required are so complex that they are impractical, but a Monte Carlo approach is straightforward.