A new multitest correction (SGoF) that increases its statistical power when increasing the number of tests.
A new multitest correction (SGoF) that increases its statistical power when increasing the number of tests.
复制标题
一种新的最大校正(SGOF),在增加测试数量时会增加其统计能力。
DOI:
10.1186/1471-2105-10-209
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发表时间:
2009-07-08
影响因子:
3
通讯作者:
Rolán-Alvarez E
中科院分区:
文献类型:
--
作者:
Carvajal-Rodríguez A;de Uña-Alvarez J;Rolán-Alvarez E
The detection of true significant cases under multiple testing is becoming a fundamental issue when analyzing high-dimensional biological data. Unfortunately, known multitest adjustments reduce their statistical power as the number of tests increase. We propose a new multitest adjustment, based on a sequential goodness of fit metatest (SGoF), which increases its statistical power with the number of tests. The method is compared with Bonferroni and FDR-based alternatives by simulating a multitest context via two different kinds of tests: 1) one-sample t-test, and 2) homogeneity G-test. It is shown that SGoF behaves especially well with small sample sizes when 1) the alternative hypothesis is weakly to moderately deviated from the null model, 2) there are widespread effects through the family of tests, and 3) the number of tests is large. Therefore, SGoF should become an important tool for multitest adjustment when working with high-dimensional biological data.
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DOI:
10.1097/00001648-199001000-00010
发表时间:
1990-01-01
期刊:
Epidemiology (Cambridge, Mass.)
影响因子:
--
作者:
Rothman, K J
通讯作者:
Rothman, K J
影响因子:
64.8
作者:
Clark, Andrew G.;Eisen, Michael B.;MacCallum, Iain
通讯作者:
MacCallum, Iain
影响因子:
3
作者:
Broberg, P
通讯作者:
Broberg, P
影响因子:
10.7
作者:
Guindon, S;Black, M;Rodrigo, A
通讯作者:
Rodrigo, A
DOI:
10.1111/j.2517-6161.1995.tb02031.x
发表时间:
1995-01-01
影响因子:
5.8
作者:
BENJAMINI, Y;HOCHBERG, Y
通讯作者:
HOCHBERG, Y