Pages that link to "Item:Q3008856"
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The following pages link to Survival Analysis with Error-Prone Time-Varying Covariates: A Risk Set Calibration Approach (Q3008856):
Displaying 15 items.
- RRC (Q52845) (← links)
- Censored count data regression with missing censoring information (Q2233576) (← links)
- Bias correction methods for misclassified covariates in the Cox model: comparison of five correction methods by simulation and data analysis (Q2320849) (← links)
- The gamma beta ratio distribution (Q2427784) (← links)
- Hazard ratio estimation for biomarker-calibrated dietary exposures (Q2912331) (← links)
- Covariate measurement error correction methods in mediation analysis with failure time data (Q3465360) (← links)
- Measurement Error Case Series Models With Application to Infection-Cardiovascular Risk in Older Patients on Dialysis (Q4904710) (← links)
- Proportional Hazards Model With Covariate Measurement Error and Instrumental Variables (Q4975633) (← links)
- Much room for optimism on measuring diet, preventing cancer and cardiovascular disease, and correcting for measurement error – discussion of the paper by R. L. Prentice and Y. Huang (Q5879950) (← links)
- Semiparametric regression calibration for general hazard models in survival analysis with covariate measurement error; surprising performance under linear hazard (Q6074500) (← links)
- Estimation and inference for exposure effects with latency in the Cox proportional hazards model in the presence of exposure measurement error (Q6104140) (← links)
- Asynchronous and error-prone longitudinal data analysis via functional calibration (Q6589281) (← links)
- There is no impact of exposure measurement error on latency estimation in linear models (Q6625935) (← links)
- Approximate profile likelihood estimation for Cox regression with covariate measurement error (Q6626745) (← links)
- STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology. I: Basic theory and simple methods of adjustment (Q6627420) (← links)
