Sex differences in sum scores may be hard to interpret: the importance of measurement invariance.

In most assessment instruments, distinct items are designed to measure a trait, and the sum score of these items serves as an approximation of an individual's trait score. In interpreting group differences with respect to sum scores, the instrument should measure the same underlying trait across groups (e.g., male/female, young/old). Differences with respect to the sum score should accurately reflect differences in the latent trait of interest. A necessary condition for this is that the instrument is measurement invariant. In the current study, the authors illustrate a stepwise approach for testing measurement invariance with respect to sex in a four-item instrument designed to assess disordered eating behavior in a large epidemiological sample (1,195 men and 1,507 women). This approach can be applied to other phenotypes for which group differences are expected. Any analysis of such variables may be subject to measurement bias if a lack of measurement invariance between grouping variables goes undetected.