Measurement error and ANCOVA: Functional and structural relationship approaches

This article discusses alternative procedures to the standardF-test for ANCOVA in case the covariate is measured with error. Both a functional and a structural relationship approach are described. Examples of both types of analysis are given for the simple two-group design. Several cases are discussed and special attention is given to issues of model identifiability. An approximate statistical test based on the functional relationship approach is described. On the basis of Monte Carlo simulation results it is concluded that this testing procedure is to be preferred to the conventionalF-test of the ANCOVA null hypothesis. It is shown how the standard null hypothesis may be tested in a structural relationship approach. It is concluded that some knowledge of the reliability of the covariate is necessary in order to obtain meaningful results.