AMS Review

, Volume 3, Issue 1, pp 18–23

Conceptual clarity in measurement—Constructs, composites, and causes: a commentary on Lee, Cadogan and Chamberlain


DOI: 10.1007/s13162-013-0036-y

Cite this article as:
Howell, R.D. AMS Rev (2013) 3: 18. doi:10.1007/s13162-013-0036-y


In an insightful and important article, Lee et al. (2013, this issue) clearly point out the problems with so-called formative measurement. In particular, they suggest that the MIMIC model formulation, as currently conceptualized, does not provide a solution. Their central thesis is that, in a MIMIC model, the supposedly formatively measured latent variable is empirically a reflective latent variable depending entirely on the endogenous variables included. They then look at composite variables as a possible solution. This commentary seeks to reinforce their central thesis, providing additional evidence and support. I also attempt to clarify the distinction between two types of models discussed in the article as MIMIC models. I then examine the use of composite variables, focusing on potential information loss and issues concerning conceptual clarity. I conclude that composite variables should not be routinely employed in theory testing research, and their use must be clearly justified.


Formative measurementReflective measurementComposite variables

Copyright information

© Academy of Marketing Science 2013

Authors and Affiliations

  1. 1.James L. Johnson Business Administration, Rawls College of BusinessTexas Tech UniversityLubbockUSA