Slow spindle percentage (SSP) was compared among and within groups for topography and night section by means of Chi-square tests with Bonferroni correction for multiple comparisons. Bonferroni correction for multiple comparisons (Holm, 1979). A Bonferroni correction factor can be used to correct for multi-hypothesis testing; the p value threshold deemed significant for an individual test is divided by the number of tests con- To avoid this, the level of statistical significance of correlation coefficients should be adjusted. The Bonferroni correction tends to be a bit too conservative. For example, in the example above, with 20 tests and = 0:05, you’d only reject a null hypothesis if the p-value is less than 0.0025. Case–control studies A Bonferroni correction factor can be used to correct for multi-hypothesis testing; the p value threshold deemed significant for an individual test is divided by the number of tests conducted, thereby accounting for spurious significance owing to multiple testing over all the categories in the GO database. 当使用了Bonferroni校正后，即使我们进行了10000次饮食实验，却只有发现2个假阳性的结果，Bonferroni是一种非常严格的校正。 错误发现率(FDR) 在许多情况下，要求FWER是0.05没多大意义，因为它太严格了。 Correct, that is what I am using the Dunn test for. Statistical significance was assumed for two-tailed p-values <0.05. The Bonferroni correction sets the signi cance cut-o at =n. Threshold levels of significance for correlation coefficients were adjusted for multiple comparisons in a set of k correlation coefficients (k = 1, 5, 10, 20, 50, 100) by Bonferroni's correction. The easiest correction is the Bonferroni adjustment, in which you divide 0.05 by the number of tests undertaken; but this is conservative and instead increases the risk of a false negative result (not rejecting a null hypothesis that is false, a type II error). Since I am comparing multiple groups (although I am just comparing 2 at a time using the Mann-Whitney test), the p-value obtained from the Mann-Whitney test needs to be multiplied by 9 for a Bonferroni correction (or alternatively, I need to divide the alpha value by 9). “People’s names” category and “Trouble. The STATQUEST filtering algorithm was then applied to all putative search results to obtain a measure of the statistical reliability (confidence score) for each candidate identification (cutoff p-value ≤.15, corresponding to an 85% or greater likelihood of being a correct match). These pairs included those where. high (e.g. Bonferroni correction: Bonferroni-korrektion Borel distribution: Borelfordeling Borel set: Borelmængde boundary: rand boundary condition: randbetingelse boundary point: randpunkt bounded: begrænset bracket: parentes branch and bound: forgren og begræns branching process: forgreningsproces Brownian motion: Brownsk bevægelse Database. Bonferroni correction (multiply p with number of tests) Benjamini-Hochberg correction (based on the FDR) adjusted p-value<0.05 (<0.1) significantly differentially ... Josh Starmer (StatQuest) 9 Potential for surveying the entire transcriptome, including novel, un-annotated regions. The Bonferroni correction was specifically applied in 51 (36%) of articles, other types of correction such as the Bonferroni‐Holm method, standard Abbott formula, the false discovery rate, the Hochberg method, or an alternative conservative post‐hoc procedure, such as … To demonstrate So I am comparing 9 groups in total. correspondence between category and item was.