Conventional methods and analyses view measurement error as random. A scenario is presented where a variable was measured with systematic error. Mixture models with systematic parameter constraints were used to test hypotheses in the context of general linear models; this accommodated the heterogeneity arising due to systematic measurement error.
Liu, Min; Hancock, Gregory R.; and Harring, Jeffrey R.
"Using Finite Mixture Modeling to Deal with Systematic Measurement Error: A Case Study,"
Journal of Modern Applied Statistical Methods: Vol. 10
, Article 22.
Available at: http://digitalcommons.wayne.edu/jmasm/vol10/iss1/22