Samples in many cell-based experiments are matched/paired but taking this into account does not always increase power of statistical tests for differences in means.

ABSTRACT: Power of statistical tests for differences in means is the probability of obtaining a statistically significant p value when means differ. When samples in experimental replicates come from a single cell culture, they are matched or paired because they share between-trials biological variability. This can cause positive correlation between values from conditions in a replicate. Correlation can also be caused in otherwise independent samples by shared technical variability. However, correlation is reduced by noise that affects samples individually. I investigated how to maximize power in experiments with two conditions over a range of correlations. Normalizing data to control increases the rate of false positives, if Student's t test is used. Paired t tests, theoreticall

SUBMITTER: Zweifach A 

PROVIDER: S-EPMC10881176 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature