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

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

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 mismeasured data will differ from the corresponding analysis based on the "true" covariate. Statistical analysis can be adjusted for measurement error, however various methods exhibit a tradeo between convenience...

A moment-adjusted imputation method for measurement error models.

Studies of clinical characteristics frequently measure covariates with a single observation. This may be a mismeasured version of the "true" phenomenon due to sources of variability like biological fluctuations and device error. Descriptive analyses and outcome models that are based on mismeasured data generally will not reflect the corresponding analyses based on the "true" covariate. Many sta...

Logistic Regression for Multivariate Longitudinal Ordinal Data

A comparison of regression calibration, moment reconstruction and imputation for adjusting for covariate measurement error in regression.

Regression calibration (RC) is a popular method for estimating regression coefficients when one or more continuous explanatory variables, X, are measured with an error. In this method, the mismeasured covariate, W, is substituted by the expectation E(X|W), based on the assumption that the error in the measurement of X is non-differential. Using simulations, we compare three versions of RC with ...

Commentary: dealing with measurement error: multiple imputation or regression calibration?

Cole et al. in this issue 2 propose that MI may also be useful in dealing with a second problem rife in epidemiology: exposure measurement error, which typically causes underestimation of exposure–disease associations (regression dilution bias). 3 They coin the acronym MIME (multiple imputation for measurement error) and show that this method can indeed remove regression dilution bias. How wide...