Bias correction methods for misclassified covariates in the Cox model: comparison of five correction methods by simulation and data analysis
DOI10.1080/15598608.2013.772830zbMath1423.62133OpenAlexW2072457708WikidataQ30670443 ScholiaQ30670443MaRDI QIDQ2320849
Mehul D. Patel, Kathryn M. Rose, Ya-Lin Chiu, Heejung Bang, Jay S. Kaufman, Gerardo Heiss
Publication date: 27 August 2019
Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc3780447
measurement errormisclassificationCox proportional hazards regressionARICchildhood SESrecalled error
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)
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- Asymptotic variance estimation for the misclassification SIMEX
- Survival Analysis with Error-Prone Time-Varying Covariates: A Risk Set Calibration Approach
- Corrected score function for errors-in-variables models: Methodology and application to generalized linear models
- Covariate measurement errors and parameter estimation in a failure time regression model
- Measurement error in the generalised linear model
- Inference and missing data
- A NOTE ON THE CORRECTED SCORE FUNCTION ADJUSTING FOR MISCLASSIFICATION
- Simulation-Extrapolation Estimation in Parametric Measurement Error Models
- Cox Regression with Accurate Covariates Unascertainable: A Nonparametric-Correction Approach
- Fitting Parametric Counting Processes by Using Log-Linear Models
- A General Method for Dealing with Misclassification in Regression: The Misclassification SIMEX
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