Contents
What is a pairwise p-value?
Pairwise multiple comparisons tests involve the computation of a p-value for each pair of the compared groups. The p-value represents the risk of stating that an effect is statistically significant while this is not true.
Is ANOVA a pairwise?
Whereas a one-way omnibus ANOVA assesses whether a significant difference exists at all amongst the groups, pairwise comparisons can be used to determine which group differences are statistically significant.
What is a pairwise t test?
A paired t-test is used when we are interested in the difference between two variables for the same subject. Often the two variables are separated by time. Since we are ultimately concerned with the difference between two measures in one sample, the paired t-test reduces to the one sample t-test.
Which is the best description of a p value?
A p -value, or probability value, is a number describing how likely it is that your data would have occurred under the null hypothesis of your statistical test. How do you calculate a p-value?
Can ANOVA be significant when none of the pairwise t tests is?
The opposite is clearly possible: overall ANOVA can be non-significant while some of the pairwise t-tests erroneously report significant differences (i.e. those would be false positives). My question is about standard, non-adjusted for multiple comparisons t-tests.
How is the p value of a hypothesis determined?
The calculation of the p -value depends on the statistical test you are using to test your hypothesis: Different statistical tests have different assumptions and generate different test statistics. You should choose the statistical test that best fits your data and matches the effect or relationship you want to test.
When to use same cut off for p value?
However, what becomes a critical issue is that the same cut-off is used when ‘multiple’ tests are undertaken on the same case-control (or any pairwise) comparison. Here, in brevity, we present what the P value represents, and why and when it should be adjusted.