Weighted empirical adaptive variance estimators for correlated data regression

摘要: Estimating equations based on marginal generalized linear models are useful for regression modelling of correlated data, but inference and testing require reliable estimates standard errors. We introduce a class variance estimators the weighted empirical estimating functions show that an adaptive choice weights allows estimation both asymptotically by simulation in finite samples. Connections with previous bootstrap jackknife methods explored. The effect is illustrated data health effects air pollution King County, Washington.