Package: FEprovideR 1.1

Michael Kleinsasser

FEprovideR: Fixed Effects Logistic Model with High-Dimensional Parameters

A structured profile likelihood algorithm for the logistic fixed effects model and an approximate expectation maximization (EM) algorithm for the logistic mixed effects model. Based on He, K., Kalbfleisch, J.D., Li, Y. and Li, Y. (2013) <doi:10.1007/s10985-013-9264-6>.

Authors:Kevin He [aut], Wenbo Wu [aut], Michael Kleinsasser [cre]

FEprovideR_1.1.tar.gz
FEprovideR_1.1.zip(r-4.5)FEprovideR_1.1.zip(r-4.4)FEprovideR_1.1.zip(r-4.3)
FEprovideR_1.1.tgz(r-4.5-any)FEprovideR_1.1.tgz(r-4.4-any)FEprovideR_1.1.tgz(r-4.3-any)
FEprovideR_1.1.tar.gz(r-4.5-noble)FEprovideR_1.1.tar.gz(r-4.4-noble)
FEprovideR_1.1.tgz(r-4.4-emscripten)FEprovideR_1.1.tgz(r-4.3-emscripten)
FEprovideR.pdf |FEprovideR.html✨
FEprovideR/json (API)

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

Bug tracker:https://github.com/umich-biostatistics/feprovider/issues

Datasets:
  • hospital - Simulated readmissions data for 500 hospitals
  • hospital_prepared - Prepared version of simulated readmissions data for 500 hospitals

On CRAN:

Conda:

2.70 score 1 stars 1 scripts 215 downloads 5 exports 29 dependencies

Last updated 6 years agofrom:36d01cf8e5. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 08 2025
R-4.5-winOKMar 08 2025
R-4.5-macOKMar 08 2025
R-4.5-linuxOKMar 08 2025
R-4.4-winOKMar 08 2025
R-4.4-macOKMar 08 2025
R-4.4-linuxOKMar 08 2025
R-4.3-winOKMar 08 2025
R-4.3-macOKMar 08 2025

Exports:confint.fe.provfe.data.prepfe.provfunnel.SRRtest.fe.prov

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpoibinR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr