Literature DB >> 24614967

Reply to Rouder (2014): good frequentist properties raise confidence.

Adam N Sanborn1, Thomas T Hills, Michael R Dougherty, Rick P Thomas, Erica C Yu, Amber M Sprenger.   

Abstract

Established psychological results have been called into question by demonstrations that statistical significance is easy to achieve, even in the absence of an effect. One often-warned-against practice, choosing when to stop the experiment on the basis of the results, is guaranteed to produce significant results. In response to these demonstrations, Bayes factors have been proposed as an antidote to this practice, because they are invariant with respect to how an experiment was stopped. Should researchers only care about the resulting Bayes factor, without concern for how it was produced? Yu, Sprenger, Thomas, and Dougherty (2014) and Sanborn and Hills (2014) demonstrated that Bayes factors are sometimes strongly influenced by the stopping rules used. However, Rouder (2014) has provided a compelling demonstration that despite this influence, the evidence supplied by Bayes factors remains correct. Here we address why the ability to influence Bayes factors should still matter to researchers, despite the correctness of the evidence. We argue that good frequentist properties mean that results will more often agree with researchers' statistical intuitions, and good frequentist properties control the number of studies that will later be refuted. Both help raise confidence in psychological results.

Entities:  

Mesh:

Year:  2014        PMID: 24614967     DOI: 10.3758/s13423-014-0607-4

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  7 in total

1.  Measuring the prevalence of questionable research practices with incentives for truth telling.

Authors:  Leslie K John; George Loewenstein; Drazen Prelec
Journal:  Psychol Sci       Date:  2012-04-16

2.  False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant.

Authors:  Joseph P Simmons; Leif D Nelson; Uri Simonsohn
Journal:  Psychol Sci       Date:  2011-10-17

3.  A Bayesian perspective on hypothesis testing: a comment on Killeen (2005).

Authors:  Eric-Jan Wagenmakers; Peter Grünwald
Journal:  Psychol Sci       Date:  2006-07

Review 4.  The frequentist implications of optional stopping on Bayesian hypothesis tests.

Authors:  Adam N Sanborn; Thomas T Hills
Journal:  Psychon Bull Rev       Date:  2014-04

5.  When decision heuristics and science collide.

Authors:  Erica C Yu; Amber M Sprenger; Rick P Thomas; Michael R Dougherty
Journal:  Psychon Bull Rev       Date:  2014-04

Review 6.  What counts as evidence for working memory training? Problems with correlated gains and dichotomization.

Authors:  Joe W Tidwell; Michael R Dougherty; Jeffrey R Chrabaszcz; Rick P Thomas; Jorge L Mendoza
Journal:  Psychon Bull Rev       Date:  2014-06

7.  Optional stopping: no problem for Bayesians.

Authors:  Jeffrey N Rouder
Journal:  Psychon Bull Rev       Date:  2014-04
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.