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2024/7/15 -We present what the P value represents, and why and when it should be adjusted. We also show, with worked examples, how to adjust P values for multiple testing.

2024/6/24 -Generally it means you don't have any hits. Raw P-value distribution has to exceed what you'd randomly expect, oversimplifying a bit.

2024/7/23 -A hypothesis is rejected at level α if and only if its adjusted p-value is less than α. In the earlier example using equal weights, the adjusted p-values are ...

2024/7/11 -The Bonferroni correction adjusts p-values by dividing the desired significance level (α) by the number of tests (m). This yields the Bonferroni-corrected p- ...

2024/8/1 -A p-value, or statistical significance, does not measure the size of an effect or the importance of a result or evidence regarding a model or hypothesis.

2024/7/27 -Problem: adjusted p-value does not express any probability. Despite their popularity, I recommend against using adjusted p-values raw p-values adjusted p-values.

2024/7/11 -The Bonferroni test adjusts p-values and confidence intervals to account for multiple comparisons. This correction makes the significance threshold more ...

2024/8/12 -Significance is defined as the − log 10 adjusted p-value (individual variants) or HMP, where the HMP for region R is defined by Eq. 8 and adjusted by a factor ...

2024/6/13 -The plot shows that the Benjamini-Hochberg method is less conservative than the Bonferroni. The adjusted P values that are generated using the Bonferroni ...

2024/8/15 -The adjust.corr function produces correlation matrices from raw data frames and produces standard normal theory t-test based p-values for all correlations among ...