Assessing the impact of measurement error in modeling change in the absence of auxiliary data

作者：Yanez N David^*; Aljasser Ibrahim; Andre Mose; Hu Chengcheng; Juraska Michal; Lumley Thomas

来源：Communications in Statistics - Theory and Methods, 2017, 46(6): 2667-2680.

DOI：10.1080/03610926.2015.1040508

• Errors in variables
• linear regression
• measurement error variance
• measurement reliability
• method of moments
• sensitivity analysis

Measurement error is well known to cause bias in estimated regression coefficients and a loss of power for detecting associations. Methods commonly used to correct for bias often require auxiliary data. We develop a solution for investigating associations between the change in an imprecisely measured outcome and precisely measured predictors, adjusting for the baseline value of the outcome when auxiliary data are not available. We require the specification of ranges for the reliability or the measurement error variance. The solution allows one to investigate the associations for change and to assess the impact of the measurement error.

• 出版日期2017