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Detecting the spatial clustering of the exposure–response relationship (ERR) between environmental risk factors and health‐related outcomes plays important roles in disease control and prevention, such as identifying highly sensitive regions, exploring the causes of heterogeneous ERRs, and designing region‐specific health intervention measures. However, few studies have focused on this issue. A possible...
Longitudinal covariates in survival models are generally analyzed using random effects models. By framing the estimation of these survival models as a functional measurement error problem, semiparametric approaches such as the conditional score or the corrected score can be applied to find consistent estimators for survival model parameters without distributional assumptions on the random effects...
Summary Measurement errors in covariates may result in biased estimates in regression analysis. Most methods to correct this bias assume nondifferential measurement errors—i.e., that measurement errors are independent of the response variable. However, in regression models for zero‐truncated count data, the number of error‐prone covariate measurements for a given observational unit can equal its response...
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