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Yunhan Mou1, Tassos Kyriakides1,2, Scott Hummel3,4

  • 1Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA.

概括

多个值的Finkelstein-Schoenfeld测试 (FS-MT) 提供了一种灵活的方式来分析心血管试验数据与复合终点. 这种新方法通过更好地纳入非致命事件来增强标准的芬克尔斯坦-舒恩菲尔德 (FS) 测试.

相关概念视频

Behrens–Fisher Test00:57

Behrens–Fisher Test

The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
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Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

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Identifying Statistically Significant Differences: The F-Test01:14

Identifying Statistically Significant Differences: The F-Test

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Bonferroni Test01:10

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Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

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F Distribution01:19

F Distribution

The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
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