Asymptotics for linear mixed models
Explores the asymptotic behavior of parameter estimates in linear mixed models, focusing on the loglikelihood as a quadratic form in Gaussian variables.
Explores the asymptotic behavior of parameter estimates in linear mixed models, focusing on the loglikelihood as a quadratic form in Gaussian variables.
Explores statistical scenarios where the bootstrap resampling method fails to provide accurate variance estimates or confidence intervals.
Discusses why simulation summaries should focus on quantiles and robust statistics rather than moments when evaluating asymptotic approximations.
Explores the complexities and efficiency trade-offs between weighted and unweighted logistic regression in case-control study designs.