Post Hoc Analysis

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A Post Hoc Analysis is an a posteriori (i.e. after-the-fact) hypothesis testing, multiple comparison procedure, or data analysis method.



In practice, post hoc analyses are usually concerned with finding patterns and/or relationships between subgroups of sampled populations that would otherwise remain undetected and undiscovered were a scientific community to rely strictly upon a priori statistical methods. Post hoc tests — also known as a posteriori tests — greatly expand the range and capability of methods that can be applied in exploratory research. Post hoc examination strengthens induction by limiting the probability that significant effects will seem to have been discovered between subgroups of a population when none actually exist. As it is, many scientific papers are published without adequate, preventative post hoc control of the type I error rate[1].
Post hoc analysis is an important procedure without which multivariate hypothesis testing would greatly suffer, rendering the chances of discovering false positives unacceptably high. Ultimately, post hoc testing creates better informed scientists who can therefore formulate better, more efficient a priori hypotheses and research designs.