%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname phacking %global packver 0.2.1 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.2.1 Release: 1%{?dist}%{?buildtag} Summary: Sensitivity Analysis for p-Hacking in Meta-Analyses License: MIT + file LICENSE URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 4.1.0 Requires: R-core >= 4.1.0 BuildRequires: R-CRAN-RcppParallel >= 5.0.1 BuildRequires: R-CRAN-rstantools >= 2.2.0 BuildRequires: R-CRAN-rstan >= 2.18.1 BuildRequires: R-CRAN-StanHeaders >= 2.18.0 BuildRequires: R-CRAN-BH >= 1.66.0 BuildRequires: R-CRAN-RcppEigen >= 0.3.3.3.0 BuildRequires: R-CRAN-Rcpp >= 0.12.0 BuildRequires: R-CRAN-dplyr BuildRequires: R-CRAN-ggplot2 BuildRequires: R-CRAN-metabias BuildRequires: R-CRAN-metafor BuildRequires: R-methods BuildRequires: R-CRAN-purrr BuildRequires: R-CRAN-rlang BuildRequires: R-stats BuildRequires: R-stats4 BuildRequires: R-CRAN-truncnorm BuildRequires: R-CRAN-Rdpack BuildRequires: R-CRAN-rstantools Requires: R-CRAN-RcppParallel >= 5.0.1 Requires: R-CRAN-rstantools >= 2.2.0 Requires: R-CRAN-rstan >= 2.18.1 Requires: R-CRAN-Rcpp >= 0.12.0 Requires: R-CRAN-dplyr Requires: R-CRAN-ggplot2 Requires: R-CRAN-metabias Requires: R-CRAN-metafor Requires: R-methods Requires: R-CRAN-purrr Requires: R-CRAN-rlang Requires: R-stats Requires: R-stats4 Requires: R-CRAN-truncnorm Requires: R-CRAN-Rdpack Requires: R-CRAN-rstantools %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). %prep %setup -q -c -n %{packname} # fix end of executable files find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \; # prevent binary stripping [ -d %{packname}/src ] && find %{packname}/src -type f -exec \ sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true [ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \ sed -i 's@-g0@@g' {} \; || true # don't allow local prefix in executable scripts find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \; %build %install mkdir -p %{buildroot}%{rlibdir} %{_bindir}/R CMD INSTALL -l %{buildroot}%{rlibdir} %{packname} test -d %{packname}/src && (cd %{packname}/src; rm -f *.o *.so) rm -f %{buildroot}%{rlibdir}/R.css # remove buildroot from installed files find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \; %files %{rlibdir}/%{packname}