The SAS %RRC Macro: The macro %rrc uses the risk set regression calibration (RRC) method to correct the point and interval estimate of the relative risk in the Cox proportional hazard regression model for bias due to measurement error in one or more baseline or time-varying exposures, including time-varying variables that are functions of the exposure history such as the 12-month moving average exposure, cumulative average exposure, cumulative total exposure, etc. An external and internal validation study designs are available to use this macro. Technical details are given in Liao et al. (2011) and Liao et al. (2018)
Keywords for this software
References in zbMATH (referenced in 4 articles , 1 standard article )
Showing results 1 to 4 of 4.
- Bousselmi, Bilel; Dupuy, Jean-François; Karoui, Abderrazek: Censored count data regression with missing censoring information (2021)
- Linda Nab, Maarten van Smeden, Ruth H. Keogh, Rolf H.H. Groenwold: mecor: An R package for measurement error correction in linear regression models with a continuous outcome (2021) arXiv
- Bang, Heejung; Chiu, Ya-Lin; Kaufman, Jay S.; Patel, Mehul D.; Heiss, Gerardo; Rose, Kathryn M.: Bias correction methods for misclassified covariates in the Cox model: comparison of five correction methods by simulation and data analysis (2013)
- Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna: Survival analysis with error-prone time-varying covariates: a risk set calibration approach (2011)