%A Krefeld-Schwalb,Antonia
%A Witte,Erich H.
%A Zenker,Frank
%D 2018
%J Frontiers in Psychology
%C
%F
%G English
%K inferential statistics,t-test,Wald-criterion,likelihood,Bayes Theorem,Research Program Strategy
%Q
%R 10.3389/fpsyg.2018.00460
%W
%L
%N 460
%M
%P
%7
%8 2018-April-24
%9 Methods
%#
%! HYPOTHESES TESTS DEMAND TRUSTWORTHY DATA
%*
%<
%T Hypothesis-Testing Demands Trustworthy Data—A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy
%U https://www.frontiersin.org/article/10.3389/fpsyg.2018.00460
%V 9
%0 JOURNAL ARTICLE
%@ 1664-1078
%X In psychology as elsewhere, the main statistical inference strategy to establish empirical effects is null-hypothesis significance testing (NHST). The recent failure to replicate allegedly well-established NHST-results, however, implies that such results lack sufficient statistical power, and thus feature unacceptably high error-rates. Using data-simulation to estimate the error-rates of NHST-results, we advocate the research program strategy (RPS) as a superior methodology. RPS integrates Frequentist with Bayesian inference elements, and leads from a preliminary discovery against a (random) H0-hypothesis to a statistical H1-verification. Not only do RPS-results feature significantly lower error-rates than NHST-results, RPS also addresses key-deficits of a “pure” Frequentist and a standard Bayesian approach. In particular, RPS aggregates underpowered results safely. RPS therefore provides a tool to regain the trust the discipline had lost along the ongoing replicability-crisis.