MIGEE: Impute Missing Values and Fitting Linear Mixed Effect Model
Implements methods for estimating generalized estimating equations (GEE) with advanced options for flexible modeling and handling missing data. This package provides tools to fit and analyze GEE models for longitudinal data, allowing users to address missingness using a variety of imputation techniques. It supports both univariate and multivariate modeling, visualization of missing data patterns, and facilitates the transformation of data for efficient statistical analysis. Designed for researchers working with complex datasets, it ensures robust estimation and inference in longitudinal and clustered data settings.
| Version: |
0.1.0 |
| Depends: |
R (≥ 2.10) |
| Imports: |
mice, VIM, ggplot2, lme4, ggeffects, dplyr, readr, reshape2 |
| Published: |
2024-12-05 |
| DOI: |
10.32614/CRAN.package.MIGEE |
| Author: |
Atanu Bhattacharjee [aut, cre, ctb],
Gajendra Kumar Vishwakarma [aut, ctb],
Neelesh Kumar [aut, ctb] |
| Maintainer: |
Atanu Bhattacharjee <atanustat at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| CRAN checks: |
MIGEE results |
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