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

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Hypothesis-testing demands trustworthy data-a simulation approach to inferential statistics advocating the research program strategy. / Krefeld-Schwalb, Antonia; Witte, Erich H.; Zenker, Frank.

I: Frontiers in Psychology, Vol. 9, Nr. APR, 460, 24.04.2018.

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

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T1 - Hypothesis-testing demands trustworthy data-a simulation approach to inferential statistics advocating the research program strategy

AU - Krefeld-Schwalb, Antonia

AU - Witte, Erich H.

AU - Zenker, Frank

PY - 2018/4/24

Y1 - 2018/4/24

N2 - 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.

AB - 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.

KW - Bayes' theorem

KW - Inferential statistics

KW - Likelihood

KW - Replication

KW - Research program strategy

KW - T-test

KW - Wald criterion

U2 - 10.3389/fpsyg.2018.00460

DO - 10.3389/fpsyg.2018.00460

M3 - Article

C2 - 29740363

AN - SCOPUS:85045933568

VL - 9

JO - Frontiers in Psychology

JF - Frontiers in Psychology

SN - 1664-1078

IS - APR

M1 - 460

ER -