Statistical model selection: the alternative to null hypothesis testing

The statistic p(rep) estimates the probability of replicating an effect. It captures traditional publication criteria for signal-to-noise ratio, while avoiding parametric inference and the resulting Bayesian dilemma. In concert with effect size and…

This paper presents a review and critique of statistical null hypothesis testing in ecological studies in general, and wildlife studies in particular, and describes an alternative. Our review of Ecology and the Journal of Wildlife Management found…

The many criticisms of null hypothesis testing suggest when it is not useful and what it should not be used for. This article explores when and why its use is appropriate. Null hypothesis testing is insufficient when size of effect is important, but…

A controversy concerning the usefulness of "null" hypothesis tests in scientific inference has continued in articles within psychology since 1960 and has recently come to a head, with serious proposals offered for a test ban or something close to…

Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously. This poses new difficulties for the statistician, but also opens new…

Comments on the article by R. L. Hagen (see record 1997-02239-002) on null hypothesis testing. Hagen's article is constrained to the logic of deduction from an already formulated null hypothesis and the scientific conclusions that are validly drawn…

I disagree with several of Chow's traditional descriptions and justifications of null hypothesis testing: (1) accepting the null hypothesis whenever p > .05; (2) random sampling from a population; (3) the frequentist interpretation of probability;…

Comments on an article by Peter R. Killeen (see record 2005-04800-001). We appreciate Killeen's discussion about the shortcomings of classical hypothesis testing. However, any measure that is no more than a simple transformation of the classical p…

Null-hypothesis significance testing remains the standard inferential tool in cognitive science despite its serious disadvantages. Primary among these is the fact that the resulting probability value does not tell the researcher what he or she…

Null-hypothesis significance testing remains the standard inferential tool in cognitive science despite its serious disadvantages. Primary among these is the fact that the resulting probability value does not tell the researcher what he or she…