We consider semiparametric transition measurement error models for longitudinal data, where one of the covariates is measured with error in transition models, and no distributional assumption is made for the underlying unobserved covariate. An estimating equation approach based on the pseudo conditional score method is proposed. We show the resulting estimators of the regression coefficients are consistent and asymptotically normal. We also discuss the issue of efficiency loss. Simulation studies are conducted to examine the finite-sample performance of our estimators. The longitudinal AIDS Costs and Services Utilization Survey data are analyzed for illustration
In large cohort studies, it often happens that some covariates are expensive to measure and hence on...
Estimation of the mean response in a longitudinal regression model can be based on a model which rel...
Informative drop-out arises in longitudinal studies when the subject’s follow-up time depends on the...
We consider semiparametric transition measurement error models for longitudinal data, where one of t...
We consider semiparametric transition measurement error models for longitudinal data, where one cova...
We propose a new class of models, transition measurement error models, to model longitudinal data wh...
We propose a new class of models, transition measurement error models, to study the effects of covar...
We study joint modeling of survival and longitudinal data. There are two regression models of inter...
[[abstract]]Longitudinal covariates in survival models are generally analyzed using random effects m...
Longitudinal covariates in survival models are generally analyzed using random effects models. By fr...
In medical studies, it is often of interest to characterize the relationship between a time-to-event...
A logistic model relating the rates of transition between two states to a vector of covariates is co...
In the presence of covariate measurement error with the proportional hazards model, several function...
Motivated by the need to analyze the National Longitudinal Surveys data, we propose a new semiparame...
AbstractIn many medical research studies, survival time is typically the primary outcome of interest...
In large cohort studies, it often happens that some covariates are expensive to measure and hence on...
Estimation of the mean response in a longitudinal regression model can be based on a model which rel...
Informative drop-out arises in longitudinal studies when the subject’s follow-up time depends on the...
We consider semiparametric transition measurement error models for longitudinal data, where one of t...
We consider semiparametric transition measurement error models for longitudinal data, where one cova...
We propose a new class of models, transition measurement error models, to model longitudinal data wh...
We propose a new class of models, transition measurement error models, to study the effects of covar...
We study joint modeling of survival and longitudinal data. There are two regression models of inter...
[[abstract]]Longitudinal covariates in survival models are generally analyzed using random effects m...
Longitudinal covariates in survival models are generally analyzed using random effects models. By fr...
In medical studies, it is often of interest to characterize the relationship between a time-to-event...
A logistic model relating the rates of transition between two states to a vector of covariates is co...
In the presence of covariate measurement error with the proportional hazards model, several function...
Motivated by the need to analyze the National Longitudinal Surveys data, we propose a new semiparame...
AbstractIn many medical research studies, survival time is typically the primary outcome of interest...
In large cohort studies, it often happens that some covariates are expensive to measure and hence on...
Estimation of the mean response in a longitudinal regression model can be based on a model which rel...
Informative drop-out arises in longitudinal studies when the subject’s follow-up time depends on the...