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This package was removed from CRAN on 2022-09-06. Its history is shown below.
Reason: check problems were not corrected in time
Details below reflect version 1.0, its last release before removal.

mixEMM

1.0

A Mixed-Effects Model for Analyzing Cluster-Level Non-Ignorable Missing Data

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Overview

About
Maintained by Lin S. Chen1 releasesCRAN page ↗

Contains functions for estimating a mixed-effects model for clustered data (or batch-processed data) with cluster-level (or batch- level) missing values in the outcome, i.e., the outcomes of some clusters are either all observed or missing altogether. The model is developed for analyzing incomplete data from labeling-based quantitative proteomics experiments but is not limited to this type of data. We used an expectation conditional maximization (ECM) algorithm for model estimation. The cluster-level missingness may depend on the average value of the outcome in the cluster (missing not at random).

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Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.3.0 released · 2023-04-21
  • archivedRemoved from CRAN
    2022-09-06
    check problems were not corrected in time
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • 1.0
    2017-06-08
  • R
    R 3.4.0 released · 2017-04-21

Package metadata

Total releases
1
License
GPL
Bundled data
0.9 KB / 1 file
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citation("mixEMM")
Chen, L. S., Wang, P., & Wang, a. J. (n.d.). mixEMM: A Mixed-Effects Model for Analyzing Cluster-Level Non-Ignorable Missing Data (Version 1.0) [Computer software]. Retrieved August 13, 2026, from https://CRAN.R-project.org/package=mixEMM

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APA

Balamuta, J. J. (2026). R Observatory: Metrics for mixEMM version 1.0 [Data set]. HJJB, LLC. Data release v2026-08-11. https://doi.org/10.5281/zenodo.21843040

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