Marsman Maarten, Schönbrodt Felix D, Morey Richard D, Yao Yuling, Gelman Andrew, Wagenmakers Eric-Jan
Department of Psychology , University of Amsterdam , Amsterdam , The Netherlands.
Department of Psychology , Ludwig-Maximilians-Universität München , Munchen , Germany.
R Soc Open Sci. 2017 Jan 18;4(1):160426. doi: 10.1098/rsos.160426. eCollection 2017 Jan.
We applied three Bayesian methods to reanalyse the preregistered contributions to the special issue 'Replications of Important Results in Social Psychology' (Nosek & Lakens. 2014 Registered reports: a method to increase the credibility of published results. , 137-141. (doi:10.1027/1864-9335/a000192)). First, individual-experiment Bayesian parameter estimation revealed that for directed effect size measures, only three out of 44 central 95% credible intervals did not overlap with zero and fell in the expected direction. For undirected effect size measures, only four out of 59 credible intervals contained values greater than [Formula: see text] (10% of variance explained) and only 19 intervals contained values larger than [Formula: see text]. Second, a Bayesian random-effects meta-analysis for all 38 -tests showed that only one out of the 38 hierarchically estimated credible intervals did not overlap with zero and fell in the expected direction. Third, a Bayes factor hypothesis test was used to quantify the evidence for the null hypothesis against a default one-sided alternative. Only seven out of 60 Bayes factors indicated non-anecdotal support in favour of the alternative hypothesis ([Formula: see text]), whereas 51 Bayes factors indicated at least some support for the null hypothesis. We hope that future analyses of replication success will embrace a more inclusive statistical approach by adopting a wider range of complementary techniques.
我们应用了三种贝叶斯方法,对《社会心理学重要结果的重复验证》特刊(诺塞克和拉肯斯,2014年《注册报告:提高已发表结果可信度的一种方法》,第137 - 141页,doi:10.1027/1864 - 9335/a000192)中预先注册的研究成果进行重新分析。首先,个体实验的贝叶斯参数估计表明,对于定向效应量指标,44个中心95%可信区间中只有3个与零不重叠且落在预期方向。对于非定向效应量指标,59个可信区间中只有4个包含大于[公式:见原文](解释方差的10%)的值,只有19个区间包含大于[公式:见原文]的值。其次,对所有38项检验进行的贝叶斯随机效应荟萃分析表明,38个分层估计的可信区间中只有1个与零不重叠且落在预期方向。第三,使用贝叶斯因子假设检验来量化原假设相对于默认单侧备择假设的证据。60个贝叶斯因子中只有7个表明有非轶事性证据支持备择假设([公式:见原文]),而51个贝叶斯因子表明至少有一些证据支持原假设。我们希望未来对重复验证成功的分析将通过采用更广泛的互补技术,采用更具包容性的统计方法。