Package: MIIPW 0.1.1

MIIPW: IPW and Mean Score Methods for Time-Course Missing Data

Contains functions for data analysis of Repeated measurement using GEE. Data may contain missing value in response and covariates. For parameter estimation through Fisher Scoring algorithm, Mean Score and Inverse Probability Weighted method combining with Multiple Imputation are used when there is missing value in covariates/response. Reference for mean score method, inverse probability weighted method is Wang et al(2007)<doi:10.1093/biostatistics/kxl024>.

Authors:Atanu Bhattacharjee [aut, cre, ctb], Bhrigu Kumar Rajbongshi [aut, ctb], Gajendra K Vishwakarma [aut, ctb]

MIIPW_0.1.1.tar.gz
MIIPW_0.1.1.zip(r-4.5)MIIPW_0.1.1.zip(r-4.4)MIIPW_0.1.1.zip(r-4.3)
MIIPW_0.1.1.tgz(r-4.5-any)MIIPW_0.1.1.tgz(r-4.4-any)MIIPW_0.1.1.tgz(r-4.3-any)
MIIPW_0.1.1.tar.gz(r-4.5-noble)MIIPW_0.1.1.tar.gz(r-4.4-noble)
MIIPW_0.1.1.tgz(r-4.4-emscripten)MIIPW_0.1.1.tgz(r-4.3-emscripten)
MIIPW.pdf |MIIPW.html
MIIPW/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 2 scripts 184 downloads 14 exports 63 dependencies

Last updated 2 years agofrom:2a74cf88f4. Checks:6 OK, 3 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 28 2025
R-4.5-winNOTEMar 28 2025
R-4.5-macNOTEMar 28 2025
R-4.5-linuxNOTEMar 28 2025
R-4.4-winOKMar 28 2025
R-4.4-macOKMar 28 2025
R-4.4-linuxOKMar 28 2025
R-4.3-winOKMar 28 2025
R-4.3-macOKMar 28 2025

Exports:AIPWMeanScoremiAIPWmiSIPWprint_ipwprint_meanscoreQICmiipwSIPWsummary_ipwsummary_meanscoreupdateALphaupdateBetaUpdatePhiupdateSandW

Dependencies:backportsbitbit64bootbroomclicliprcodetoolscpp11crayondplyrfansiforcatsforeachgenericsglmnetgluehavenhmsiteratorsjomolatticelifecyclelme4magrittrMASSMatrixmiceminqamitmlnlmenloptrnnetnumDerivordinalpanpillarpkgconfigprettyunitsprogresspurrrR6rbibutilsRcppRcppEigenRdpackreadrreformulasrlangrpartshapestringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsvroomwithr

Introduction to MIIPW

Rendered frommiipw.Rmdusingknitr::rmarkdownon Mar 28 2025.

Last update: 2023-02-13
Started: 2023-02-13