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 262 downloads 14 exports 63 dependencies

Last updated 2 years agofrom:2a74cf88f4. Checks:5 OK, 3 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 26 2025
R-4.5-winNOTEFeb 26 2025
R-4.5-macNOTEFeb 26 2025
R-4.5-linuxNOTEFeb 26 2025
R-4.4-winOKFeb 26 2025
R-4.4-macOKFeb 26 2025
R-4.3-winOKFeb 26 2025
R-4.3-macOKFeb 26 2025

Exports:AIPWMeanScoremiAIPWmiSIPWprint_ipwprint_meanscoreQICmiipwSIPWsummary_ipwsummary_meanscoreupdateALphaupdateBetaUpdatePhiupdateSandW

Dependencies:backportsbitbit64bootbroomclicliprcodetoolscpp11crayondplyrfansiforcatsforeachgenericsglmnetgluehavenhmsiteratorsjomolatticelifecyclelme4magrittrMASSMatrixmiceminqamitmlnlmenloptrnnetnumDerivordinalpanpillarpkgconfigprettyunitsprogresspurrrR6rbibutilsRcppRcppEigenRdpackreadrreformulasrlangrpartshapestringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsvroomwithr

Introduction to MIIPW

Rendered frommiipw.Rmdusingknitr::rmarkdownon Feb 26 2025.

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