Package: GFDsurv 0.1.1

GFDsurv: Tests for Survival Data in General Factorial Designs

Implemented are three Wald-type statistic and respective permuted versions for null hypotheses formulated in terms of cumulative hazard rate functions, medians and the concordance measure, respectively, in the general framework of survival factorial designs with possibly heterogeneous survival and/or censoring distributions, for crossed designs with an arbitrary number of factors and nested designs with up to three factors. Ditzhaus, Dobler and Pauly (2020) <doi:10.1177/0962280220980784> Ditzhaus, Janssen, Pauly (2020) <arxiv:2004.10818v2> Dobler and Pauly (2019) <doi:10.1177/0962280219831316>.

Authors:Marc Ditzhaus [aut], Dennis Dobler [aut], Markus Pauly [aut], Philipp Steinhauer [aut], Merle Munko [aut, cre]

GFDsurv_0.1.1.tar.gz
GFDsurv_0.1.1.zip(r-4.5)GFDsurv_0.1.1.zip(r-4.4)GFDsurv_0.1.1.zip(r-4.3)
GFDsurv_0.1.1.tgz(r-4.4-any)GFDsurv_0.1.1.tgz(r-4.3-any)
GFDsurv_0.1.1.tar.gz(r-4.5-noble)GFDsurv_0.1.1.tar.gz(r-4.4-noble)
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GFDsurv.pdf |GFDsurv.html
GFDsurv/json (API)

# Install 'GFDsurv' in R:
install.packages('GFDsurv', repos = c('https://merlemunko.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/philippsteinhauer/gfdsurv/issues

On CRAN:

2.00 score 248 downloads 4 exports 119 dependencies

Last updated 2 years agofrom:77a9941e40. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winOKNov 16 2024
R-4.5-linuxOKNov 16 2024
R-4.4-winOKNov 16 2024
R-4.4-macOKNov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:casanovacopsanovaGFDsurvGUImedsanova

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDataclicolorspacecommonmarkcorrplotcowplotcpp11crayoncurldata.tableDerivdigestdoBydplyrevaluateexactRankTestsfansifarverfastmapfontawesomeFormulafsgenericsggplot2ggpubrggrepelggsciggsignifggtextgluegridExtragridtextgtablehighrhtmltoolshtmlwidgetshttpuvisobandjpegjquerylibjsonlitekm.ciKMsurvknitrlabelinglaterlatticelifecyclelme4magicmagrittrmarkdownMASSMatrixMatrixModelsmaxstatmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpngpolynompromisespurrrquantregR6rappdirsRColorBrewerRcppRcppEigenrlangrmarkdownrstatixsassscalesshinyshinyjsshinythemessourcetoolsSparseMstringistringrsurvivalsurvminersurvMisctibbletidyrtidyselecttinytextippyutf8vctrsviridisLitewithrxfunxml2xtableyamlzoo