Pages that link to "Item:Q3008858"

The following pages link to Simultaneous Inference and Bias Analysis for Longitudinal Data with Covariate Measurement Error and Missing Responses (Q3008858):

Displaying 16 items.

• Analysis of bivariate zero inflated count data with missing responses (Q276972) (← links)
• Corrected empirical likelihood for a class of generalized linear measurement error models (Q887052) (← links)
• A pairwise likelihood approach for longitudinal data with missing observations in both response and covariates (Q1615132) (← links)
• Using structural equation modelling to detect measurement bias and response shift in longitudinal data (Q1633178) (← links)
• Simultaneous mean and covariance estimation of partially linear models for longitudinal data with missing responses and covariate measurement error (Q1659463) (← links)
• Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study (Q2308441) (← links)
• Asymptotic theory for longitudinal data with missing responses adjusted by inverse probability weights (Q2322943) (← links)
• Covariate decomposition methods for longitudinal missing-at-random data and predictors associated with subject-specific effects (Q2804161) (← links)
• A functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error (Q3224222) (← links)
• Variable selection and inference procedures for marginal analysis of longitudinal data with missing observations and covariate measurement error (Q3463396) (← links)
• Doubly robust estimation of partially linear models for longitudinal data with dropouts and measurement error in covariates (Q4639150) (← links)
• Quantile regression in longitudinal studies with dropouts and measurement errors (Q5221550) (← links)
• Quantile regression-based Bayesian semiparametric mixed-effects models for longitudinal data with non-normal, missing and mismeasured covariate (Q5222401) (← links)
• Expected Estimating Equations for Missing Data, Measurement Error, and Misclassification, with Application to Longitudinal Nonignorable Missing Data (Q5450458) (← links)
• A spatio-temporal model for the analysis and prediction of fine particulate matter concentration in Beijing (Q6626372) (← links)
• Parametric regression analysis with covariate misclassification in main study/validation study designs (Q6637187) (← links)