File R-compositeReliabilityInNestedDesigns.spec of Package R-compositeReliabilityInNestedDesigns

# Automatically generated by CRAN2OBS
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# Spec file for package compositeReliabilityInNestedDesigns 
# 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  compositeReliabilityInNestedDesigns 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.0.4 
Release:        0 
Summary:        Optimizing the Composite Reliability in Multivariate Nested Designs 
Group:          Development/Libraries/Other 
License:        GPL (>= 3) 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         compositeReliabilityInNestedDesigns_1.0.4.tar.gz 
Requires:       R-base 
Requires:	R-dplyr
Requires:	R-ggplot2
Requires:	R-lme4
Requires:	R-magrittr
Requires:	R-plyr
Requires:	R-psych
Requires:	R-reshape2
Requires:	R-tidyr
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Requires:	R-minqa
Requires:	R-nloptr
Requires:	R-reformulas
Requires:	R-Rcpp
Requires:	R-RcppEigen
Requires:	R-mnormt
Requires:	R-GPArotation
Requires:	R-stringr
Requires:	R-truncnorm
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Requires:	R-future.apply
Requires:	R-RcppArmadillo
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Requires:	R-RColorBrewer
Requires:	R-viridisLite
Requires:	R-stringi
Requires:	R-pkgconfig
Requires:	R-digest
Requires:	R-listenv
Requires:	R-parallelly
 
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
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%description 
The reliability of assessment tools is a crucial aspect of monitoring 
student performance in various educational settings. It ensures that 
the assessment outcomes accurately reflect a student's true level of 
performance. However, when assessments are combined, determining 
composite reliability can be challenging, especially for naturalistic 
and unbalanced datasets in nested design as is often the case for 
Workplace-Based Assessments. This package is designed to estimate 
composite reliability in nested designs using multivariate 
generalizability theory and enhance the analysis of assessment data. 
The package allows for the inclusion of weight per assessment type and 
produces extensive G- and D-study results with graphical 
interpretations, and options to find the set of weights that maximizes 
the composite reliability or minimizes the standard error of 
measurement (SEM). 
 
%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
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog