A simple test for random effects in regression models

• 成果类型: Article
• 署名作者: Wood, Simon N.
• 署名单位: University of Bath
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/ast038
• 发表日期: 2013
• 页码: 10051010
• 关键词: linear mixed models; likelihood ratio tests; variance-components

摘要

Testing that random effects are zero is difficult, because the null hypothesis restricts the corresponding variance parameter to the edge of the feasible parameter space. In the context of generalized linear mixed models, this paper exploits the link between random effects and penalized regression to develop a simple test for a zero effect. The idea is to treat the variance components not being tested as fixed at their estimates and then to express the likelihood ratio as a readily computed quadratic form in the predicted values of the random effects. Under the null hypothesis this has the distribution of a weighted sum of squares of independent standard normal random variables. The test can be used with generalized linear mixed models, including those estimated by penalized quasilikelihood.