A Moment-Adjusted Imputation Method for Measurement Error Models
نویسندگان
چکیده
منابع مشابه
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...
متن کاملMoment 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...
متن کاملTESTING FOR AUTOCORRELATION IN UNEQUALLY REPLICATED FUNCTIONAL MEASUREMENT ERROR MODELS
In the ordinary linear models, regressing the residuals against lagged values has been suggested as an approach to test the hypothesis of zero autocorrelation among residuals. In this paper we extend these results to the both equally and unequally replicated functionally measurement error models. We consider the equally and unequally replicated cases separately, because in the first case the re...
متن کاملMultiple-imputation for measurement-error correction.
BACKGROUND There are many methods for measurement-error correction. These methods remain rarely used despite the ubiquity of measurement error. METHODS Treating measurement error as a missing-data problem, the authors show how multiple-imputation for measurement-error (MIME) correction can be done using SAS software and evaluate the approach with a simulation experiment. RESULTS Based on hy...
متن کاملA 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 ...
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ژورنال
عنوان ژورنال: Biometrics
سال: 2011
ISSN: 0006-341X
DOI: 10.1111/j.1541-0420.2011.01569.x