| Name : R-phacking
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| Version : 0.2.1
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp154.4.1
| Date : 2024-09-18 02:55:02
|
| Group : Development/Libraries/Other
| Source RPM : R-phacking-0.2.1-lp154.4.1.src.rpm
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| Size : 1.75 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Sensitivity Analysis for p-Hacking in Meta-Analyses
|
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.\"
< doi:10.31219/osf.io/ezjsx>.]. 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).
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.4/x86_64 |
