Linear mixed models for complex survey data: implementing and evaluating pairwise likelihood
Methodology
2023-07-12 v1 Computation
Abstract
As complex-survey data becomes more widely used in health and social-science research, there is increasing interest in fitting a wider range of regression models. We describe an implementation of two-level linear mixed models in R using the pairwise composite likelihood approach of Rao and co-workers. We discuss the computational efficiency of pairwise composite likelihood and compare the estimator to the existing stagewise pseudolikelihood estimator in simulations and in data from the PISA educational survey.
Cite
@article{arxiv.2307.04944,
title = {Linear mixed models for complex survey data: implementing and evaluating pairwise likelihood},
author = {Thomas Lumley and Xudong Huang},
journal= {arXiv preprint arXiv:2307.04944},
year = {2023}
}