The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016)…

The authors of the focus article describe an important issue related to the use and interpretation of causal indicators within the context of structural equation modeling (SEM). In the focus article, the authors illustrate with simulated data the effects of omitting a causal indicator. Since SEMs are used extensively in the social and behavioral…

In this commentary, Mijke Rhemtulla, Riet van Bork, and Denny Borsboom write that they were delighted to see Bainter and Bollen's paper as a focus article in "Measurement." In their view, psychological researchers who use SEM rely too reflexively on reflective measurement, without sufficiently considering whether their indicators are…

This article is a commentary on the Focus Article, "Interpretational Confounding or Confounded Interpretations of Causal Indicators?" and a commentary that was published in issue 12(4) 2014 of "Measurement: Interdisciplinary Research & Perspectives". The authors challenge two claims: (a) Bainter and Bollen argue that the…

Building on the work of Bollen (2007) and Bollen & Bauldry (2011), Bainter and Bollen (this issue) clarifies several points of confusion in the literature regarding causal indicator models. This author would certainly agree that the effect indicator (reflective) measurement model is inappropriate for some indicators (such as the social…

This article is a commentary of a paper by Derek C. Briggs and Frederick A. Peck, "Using Learning Progressions to Design Vertical Scales That Support Coherent Inferences about Student Growth," which describes an elegant potential framework for at least beginning to address three priorities in large-scale assessment that have not been…

Cynthia Coburn and Erica Turner have made an important contribution by developing a framework to synthesize the various strands of research and theory related to data use in schools. The framework illustrates the complexity of the pathways between the adoption of a data-use intervention and the attainment of desired outcomes, and it clarifies the…

The focus article by Coburn and Turner (this issue) seeks to provide a comprehensive framework for understanding data use in the context of data-use interventions. This commentary focuses on what the authors see as a glaring omission in what is otherwise a valuable framework: the issue of "useful data." It is their contention that the usefulness…