Search Results - subject:"Regression calibration"

Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function

Kim, Kun Ho; Chao, Shih-Kang; Härdle, Wolfgang Karl - 2020

In this paper, we conduct simultaneous inference of the non-parametric part of a partially linear model when the non-parametric component is a multivariate unknown function. Based on semi-parametric estimates of the model, we construct a simultaneous confidence region of the multivariate...

Persistent link: https://www.econbiz.de/10012433252

Simultaneous inference for the partially linear model with a multivariate unknown function when the covariates are measured with errors

Kim, Kun Ho; Chao, Shih-Kang; Härdle, Wolfgang Karl - 2016

In this paper, we analyze the nonparametric part of a partially linear model when the covariates in parametric and non-parametric parts are subject to measurement errors. Based on a two-stage semi-parametric estimate, we construct a uniform con dence surface of the multivariate function for...

Persistent link: https://www.econbiz.de/10011531900

Simultaneous inference for the partially linear model with a multivariate unknown function when the covariates are measured with errors

Kim, Kun Ho; Chao, Shih-Kang; Härdle, Wolfgang - 2016

Persistent link: https://www.econbiz.de/10011518796

Improved regression calibration

Skrondal, Anders; Kuha, Jouni - London School of Economics (LSE) - 2012

form which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is … computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration approach, a general … to those obtained by maximum likelihood. Simulations suggest that improved regression calibration which is easy to …

Persistent link: https://www.econbiz.de/10010745212

Regression Calibration in Semiparametric Accelerated Failure Time Models

Yu, Menggang; Nan, Bin - 2010

. Regression calibration (RC) estimation method ( Prentice, 1982 , Biometrika 69 , 331–342) is a popular method for analyzing such …

Persistent link: https://www.econbiz.de/10009476724

Correction methods, approximate biases, and inference for misclassified data

Shieh, Meng-Shiou - 2009

misclassification/reclassification model. These correction methods use the score function approach, regression calibration and a mixture …

Persistent link: https://www.econbiz.de/10009467829

Moment adjusted imputation for multivariate measurement error data with applications to logistic regression

Thomas, Laine; Stefanski, Leonard A.; Davidian, Marie - In: Computational Statistics & Data Analysis 67 (2013) C, pp. 15-24

In clinical studies, covariates are often measured with error due to biological fluctuations, device error and other sources. Summary statistics and regression models that are based on mis-measured data will differ from the corresponding analysis based on the “true” covariate. Statistical...

Persistent link: https://www.econbiz.de/10011056576

Estimation for Generalized Linear Models When Covariates Are Subject-specific Parameters in a Mixed Model for Longitudinal Measurements

Li, Erning - 2005

, and several methods for reducing this bias have been proposed, which include regression calibration, pseudo …-expected estimating equations, and refined regression calibration (for logistic primary model only). However, these methods require a …

Persistent link: https://www.econbiz.de/10009431291

Correcting for Bias due to Misclassification when Error-prone Continuous Exposures Are Misclassified

Keogh, Ruth H.; Strawbridge, Alexander D.; White, Ian - In: Epidemiologic Methods 1 (2012) 1, pp. 189-215

regression calibration (RC), multiple imputation (MI), moment reconstruction (MR) and simulation extrapolation (SIMEX). There are …

Persistent link: https://www.econbiz.de/10014590583

Improved Regression Calibration

Skrondal, Anders; Kuha, Jouni - In: Psychometrika 77 (2012) 4, pp. 649-669

form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is … computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration approach, a general … to those obtained by maximum likelihood. Simulations suggest that improved regression calibration, which is easy to …

Persistent link: https://www.econbiz.de/10010600769