Explains why the svylme package uses maximum likelihood instead of REML for survey-weighted linear mixed models, focusing on design and sampling constraints.
A tutorial on visualizing mixed effect regression models and their uncertainty using non-parametric bootstrapping in R with ggplot2.
Explores the statistical challenges of applying linear mixed models to complex survey data with multi-stage sampling, focusing on weighting issues.
A developer introduces an experimental R package for fitting linear mixed models to complex survey data, detailing its current capabilities and limitations.
Explores using pairwise composite likelihood to fit mixed models when survey sampling and model random-effect structures differ, using genetic analysis as an example.
