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The relation between overlapping confidence intervals and p-values is a bit tricky. Under some reasonable conditions, if two 95% confidence intervals don't overlap then the p-value for testing a diffe …

The burden, SKAT, and SKAT-O tests represent 3 ways to pool information from low-frequency genetic variants so that relations of genomic loci to a biologic characteristic (phenotype) can be assessed. …

The biggest problem you have is that your analysis of pairwise correlations could severely limit your ability to understand the underlying issues. Seldom in biomedical research does one variable depen …

Remember that t-tests are based on standard errors of the means, which are smaller than the standard deviations; in your case, with 69 and 21 observations in the groups, standard errors are a good dea …

To expand on what Ben Bolker notes in a comment on another answer, the issue of what a frequentist p-value means for a regression coefficient in LASSO is not at all easy. What's the actual null hypoth …

As "equivalence testing" has a well-established meaning in statistics, you are correct that failure to reject a null hypothesis should not lead to a claim that the treatments are "equivalent" or "equa …

The Bonferroni correction (or its more powerful but equally sensitive Holm modification) controls the family-wise error rate, the chance that any of your nominally significant results is a false posit …

The task behind the question to which you link, for some unspecified reason, requires repeated subsampling of a random 15% of a data sample. That's throwing away 85% of the data each time. In general, …

The page to which you linked refers to a situation with t-tests, which aren't appropriate for your survival data. Also, your effective sample size isn't just the number of carcasses but also involves …

A lot depends on the nature of your data and your understanding of the subject matter. If it's reasonable to construct a single model for each of disease-free and overall survival among all these type …

There is nothing wrong with the mechanics of the Fisher's test. It evaluates whether there is a difference in the proportions of cases among rows/columns. In your example, you have approximately equal …

A substantial check on the important issue raised in this question is that "scientific truth" is not based on individual, isolated publications. If a result is sufficiently interesting it will prompt …

Alex (+1) has the fundamental answer: if you have categorical data the $\chi^2$ test provides a simple test of overall significance. For your data I get a p-value of 0.12, meaning that in 12% of exper …

There are two things to consider here. First, the p value reported for an individual coefficient in a standard linear regression is based on a t-test. As that test uses an estimate of the standard er …

As you recognize, the multiple testing with an adaptive design poses a risk of false-positive results (Type I error). You certainly do not want to continue adding cases and testing the hypothesis repe …