%global __brp_check_rpaths %{nil} %global packname intmed %global packver 0.1.2 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.1.2 Release: 1%{?dist}%{?buildtag} Summary: Mediation Analysis using Interventional Effects License: MIT + file LICENSE URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.5.0 Requires: R-core >= 3.5.0 BuildArch: noarch BuildRequires: R-CRAN-stringr BuildRequires: R-MASS BuildRequires: R-CRAN-mice BuildRequires: R-CRAN-dplyr BuildRequires: R-CRAN-tibble BuildRequires: R-CRAN-foreach BuildRequires: R-CRAN-doParallel Requires: R-CRAN-stringr Requires: R-MASS Requires: R-CRAN-mice Requires: R-CRAN-dplyr Requires: R-CRAN-tibble Requires: R-CRAN-foreach Requires: R-CRAN-doParallel %description Implementing the interventional effects for mediation analysis for up to 3 mediators. The methods used are based on VanderWeele, Vansteelandt and Robins (2014) , Vansteelandt and Daniel (2017) and Chan and Leung (2020; unpublished manuscript, available on request from the author of this package). Linear regression, logistic regression and Poisson regression are used for continuous, binary and count mediator/outcome variables respectively. %prep %setup -q -c -n %{packname} find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \; [ -d %{packname}/src ] && find %{packname}/src -type f -exec \ sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true %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 find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \; %files %{rlibdir}/%{packname}