New statistical metrics for multisite replication projects. (21st May 2020)
- Record Type:
- Journal Article
- Title:
- New statistical metrics for multisite replication projects. (21st May 2020)
- Main Title:
- New statistical metrics for multisite replication projects
- Authors:
- Mathur, Maya B.
VanderWeele, Tyler J. - Abstract:
- Summary: Increasingly, researchers are attempting to replicate published original studies by using large, multisite replication projects, at least 134 of which have been completed or are on going. These designs are promising to assess whether the original study is statistically consistent with the replications and to reassess the strength of evidence for the scientific effect of interest. However, existing analyses generally focus on single replications; when applied to multisite designs, they provide an incomplete view of aggregate evidence and can lead to misleading conclusions about replication success. We propose new statistical metrics representing firstly the probability that the original study's point estimate would be at least as extreme as it actually was, if in fact the original study were statistically consistent with the replications, and secondly the estimated proportion of population effects agreeing in direction with the original study. Generalized versions of the second metric enable consideration of only meaningfully strong population effects that agree in direction, or alternatively that disagree in direction, with the original study. These metrics apply when there are at least 10 replications (unless the heterogeneity estimate τ ^ = 0, in which case the metrics apply regardless of the number of replications). The first metric assumes normal population effects but appears robust to violations in simulations; the second is distribution free. We provide RSummary: Increasingly, researchers are attempting to replicate published original studies by using large, multisite replication projects, at least 134 of which have been completed or are on going. These designs are promising to assess whether the original study is statistically consistent with the replications and to reassess the strength of evidence for the scientific effect of interest. However, existing analyses generally focus on single replications; when applied to multisite designs, they provide an incomplete view of aggregate evidence and can lead to misleading conclusions about replication success. We propose new statistical metrics representing firstly the probability that the original study's point estimate would be at least as extreme as it actually was, if in fact the original study were statistically consistent with the replications, and secondly the estimated proportion of population effects agreeing in direction with the original study. Generalized versions of the second metric enable consideration of only meaningfully strong population effects that agree in direction, or alternatively that disagree in direction, with the original study. These metrics apply when there are at least 10 replications (unless the heterogeneity estimate τ ^ = 0, in which case the metrics apply regardless of the number of replications). The first metric assumes normal population effects but appears robust to violations in simulations; the second is distribution free. We provide R packages (Replicate and MetaUtility). … (more)
- Is Part Of:
- Journal of the Royal Statistical Society. Volume 183:Number 3(2020)
- Journal:
- Journal of the Royal Statistical Society
- Issue:
- Volume 183:Number 3(2020)
- Issue Display:
- Volume 183, Issue 3 (2020)
- Year:
- 2020
- Volume:
- 183
- Issue:
- 3
- Issue Sort Value:
- 2020-0183-0003-0000
- Page Start:
- 1145
- Page End:
- 1166
- Publication Date:
- 2020-05-21
- Subjects:
- Effect sizes -- Heterogeneity -- Replication -- Reproducibility
Social sciences -- Statistical methods -- Periodicals
Statistics -- Periodicals
300.15195 - Journal URLs:
- http://rss.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)1467-985X/ ↗
https://academic.oup.com/jrsssa ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/rssa.12572 ↗
- Languages:
- English
- ISSNs:
- 0964-1998
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4866.000000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 13321.xml