Package: mixEMM
Title: A Mixed-Effects Model for Analyzing Cluster-Level Non-Ignorable
        Missing Data
Version: 1.0
Date: 2017-06-06
Author: Lin S. Chen, Pei Wang, and Jiebiao Wang
Maintainer: Lin S. Chen <lchen@health.bsd.uchicago.edu>
Description: 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).
License: GPL
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-08 03:09:44 UTC; JWang
Repository: CRAN
Date/Publication: 2017-06-08 15:21:36 UTC
Built: R 4.0.2; ; 2020-07-15 16:22:34 UTC; unix
