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phacking
Sensitivity Analysis for p-Hacking in Meta-Analyses
View on CRAN: Click
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Download and install phacking package within the R console
Install from CRAN:
install.packages("phacking")
Install from Github:
library("remotes")
install_github("cran/phacking") Install by package version:
library("remotes")
install_version("phacking", "0.2.1") Attach the package and use:
library("phacking")
Maintained by
Peter Solymos
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-06-21
Latest Update: 2023-07-17
Description:
Fits right-truncated meta-analysis (RTMA), a bias correction for
the joint effects of p-hacking (i.e., manipulation of results within studies
to obtain significant, positive estimates) and traditional publication bias
(i.e., the selective publication of studies with significant, positive
results) in meta-analyses [see Mathur MB (2022). "Sensitivity analysis for
p-hacking in meta-analyses." .]. Unlike publication
bias alone, p-hacking that favors significant, positive results (termed
"affirmative") can distort the distribution of affirmative results. To
bias-correct results from affirmative studies would require strong assumptions
on the exact nature of p-hacking. In contrast, joint p-hacking and publication
bias do not distort the distribution of published nonaffirmative results when
there is stringent p-hacking (e.g., investigators who hack always eventually
obtain an affirmative result) or when there is stringent publication bias
(e.g., nonaffirmative results from hacked studies are never published). This
means that any published nonaffirmative results are from unhacked studies.
Under these assumptions, RTMA involves analyzing only the published
nonaffirmative results to essentially impute the full underlying distribution
of all results prior to selection due to p-hacking and/or publication bias.
The package also provides diagnostic plots described in Mathur (2022).
How to cite:
Peter Solymos (2022). phacking: Sensitivity Analysis for p-Hacking in Meta-Analyses. R package version 0.2.1, https://cran.r-project.org/web/packages/phacking. Accessed 17 Jul. 2026.
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Complete documentation for phacking
Functions, R codes and Examples using
the phacking R package
Some associated functions: money_priming_meta . phacking-package . phacking_meta . rtma_cdf . rtma_qqplot . z_density .
Some associated R codes: data.R . diagnostics.R . metabias-names.R . models.R . phacking-package.R . stanmodels.R . theory.R . utils.R . Full phacking package functions and examples
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