Hypothesis-testing demands trustworthy data-a simulation approach to inferential statistics advocating the research program strategy

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Bibtex

@article{f634df0f05824d73b49025bcebed1c44,
title = "Hypothesis-testing demands trustworthy data-a simulation approach to inferential statistics advocating the research program strategy",
abstract = "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 during the ongoing replicability-crisis.",
keywords = "Bayes' theorem, Inferential statistics, Likelihood, Replication, Research program strategy, T-test, Wald criterion",
author = "Antonia Krefeld-Schwalb and Witte, {Erich H.} and Frank Zenker",
year = "2018",
month = apr,
day = "24",
doi = "10.3389/fpsyg.2018.00460",
language = "English",
volume = "9",
journal = "Frontiers in Psychology",
issn = "1664-1078",
publisher = "Frontiers Media S. A.",
number = "APR",

}