jepustoFor all you fans of cluster-robust standard errors, #rstats package clubSandwich update dropped today (version 0.5.9):
http://jepusto.github.io/clubSandwich/
This version finally (FINALLY!) adds support for geepack::geeglm().
Also adds support for metafor's location-scale meta-regression models (https://metafor-project.org/doku.php/tips:different_tau2_across_subgroups) and a few bug fixes and enhancements.
Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections
Provides several cluster-robust variance estimators (i.e., sandwich estimators) for ordinary and weighted least squares linear regression models, including the bias-reduced linearization estimator introduced by Bell and McCaffrey (2002) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2002002/article/9058-eng.pdf> and developed further by Pustejovsky and Tipton (2017) <DOI:10.1080/07350015.2016.1247004>. The package includes functions for estimating the variance- covariance matrix and for testing single- and multiple- contrast hypotheses based on Wald test statistics. Tests of single regression coefficients use Satterthwaite or saddle-point corrections. Tests of multiple- contrast hypotheses use an approximation to Hotellings T-squared distribution. Methods are provided for a variety of fitted models, including lm() and mlm objects, glm(), geeglm() (from package geepack), ivreg() (from package AER), ivreg() (from package ivreg when estimated by ordinary least squares), plm() (from package plm), gls() and lme() (from nlme), lmer() (from `lme4`), robu() (from robumeta), and rma.uni() and rma.mv() (from metafor').
sam
Wolfgang Viechtbauer
Davis Vaughan
Lisa DeBruine 🏳️🌈
AERA SRMA SIG
Karandeep Singh
