File R-MRStdLCRT.spec of Package R-MRStdLCRT

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# Spec file for package MRStdLCRT 
# This file is auto-generated using information in the package source, 
# esp. Description and Summary. Improvements in that area should be 
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%global packname  MRStdLCRT 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        0.1.0 
Release:        0 
Summary:        Model-Robust Standardization for Longitudinal Cluster-Randomized Trials 
Group:          Development/Libraries/Other 
License:        MIT + file LICENSE 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         MRStdLCRT_0.1.0.tar.gz 
Requires:       R-base 
Requires:	R-reformulas
Requires:	R-dplyr
Requires:	R-tidyr
Requires:	R-rlang
Requires:	R-tidyselect
Requires:	R-gee
Requires:	R-lme4
Requires:	R-ggplot2
Requires:	R-cli
Requires:	R-generics
Requires:	R-glue
Requires:	R-lifecycle
Requires:	R-magrittr
Requires:	R-pillar
Requires:	R-R6
Requires:	R-tibble
Requires:	R-vctrs
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-S7
Requires:	R-scales
Requires:	R-withr
Requires:	R-minqa
Requires:	R-nloptr
Requires:	R-Rdpack
Requires:	R-Rcpp
Requires:	R-RcppEigen
Requires:	R-purrr
Requires:	R-stringr
Requires:	R-cpp11
Requires:	R-utf8
Requires:	R-rbibutils
Requires:	R-farver
Requires:	R-labeling
Requires:	R-RColorBrewer
Requires:	R-viridisLite
Requires:	R-stringi
Requires:	R-pkgconfig
 
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
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# BuildRequires:  tex(ae.sty) 
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BuildRequires: 	R-tidyselect
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BuildRequires: 	R-cli
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Suggests:	R-testthat
%description 
Provides estimation and leave-one-cluster-out jackknife standard errors 
for four longitudinal cluster-randomized trial estimands: horizontal 
individual average treatment effect (h-iATE), horizontal cluster 
average treatment effect (h-cATE), vertical individual average 
treatment effect (v-iATE), and vertical cluster-period average 
treatment effect (v-cATE), using unadjusted and augmented (model-robust 
standardization) estimators. The working model may be fit using linear 
mixed models for continuous outcomes or generalized estimating 
equations and generalized linear mixed models for binary outcomes. 
Period inclusion for aggregation is determined automatically: only 
periods with both treated and control clusters are included in the 
construction of the marginal means and treatment effect contrasts. See 
Fang et al. (2025) <doi:10.48550/arXiv.2507.17190>. 
 
%prep 
%setup -q -c -n %{packname} 
# the next line is needed, because we build without --clean in between two packages 
rm -rf ~/.R  
 
 
%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 
%fdupes -s %{buildroot}%{rlibdir} 
 
#%%check 
#%%{_bindir}/R CMD check %%{packname} 
 
%files 
%dir %{rlibdir}/%{packname} 
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%license %{rlibdir}/%{packname}/LICENSE
%license %{rlibdir}/%{packname}/LICENSE.md
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog 
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