Literature DB >> 26390170

In defense of causal-formative indicators: A minority report.

Kenneth A Bollen1, Adamantios Diamantopoulos2.   

Abstract

Causal-formative indicators directly affect their corresponding latent variable. They run counter to the predominant view that indicators depend on latent variables and are thus often controversial. If present, such indicators have serious implications for factor analysis, reliability theory, item response theory, structural equation models, and most measurement approaches that are based on reflective or effect indicators. Psychological Methods has published a number of influential articles on causal and formative indicators as well as launching the first major backlash against them. This article examines 7 common criticisms of these indicators distilled from the literature: (a) A construct measured with "formative" indicators does not exist independently of its indicators; (b) Such indicators are causes rather than measures; (c) They imply multiple dimensions to a construct and this is a liability; (d) They are assumed to be error-free, which is unrealistic; (e) They are inherently subject to interpretational confounding; (f) They fail proportionality constraints; and (g) Their coefficients should be set in advance and not estimated. We summarize each of these criticisms and point out the flaws in the logic and evidence marshaled in their support. The most common problems are not distinguishing between what we call causal-formative and composite-formative indicators, tautological fallacies, and highlighting issues that are common to all indicators, but presenting them as special problems of causal-formative indicators. We conclude that measurement theory needs (a) to incorporate these types of indicators, and (b) to better understand their similarities to and differences from traditional indicators. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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Year:  2015        PMID: 26390170      PMCID: PMC6670294          DOI: 10.1037/met0000056

Source DB:  PubMed          Journal:  Psychol Methods        ISSN: 1082-989X


  20 in total

1.  Assessing within- and between-family variations in an expanded measure of childhood adversity.

Authors:  Melinda I Morrill; Marc S Schulz; Michael D Nevarez; Kristopher J Preacher; Robert J Waldinger
Journal:  Psychol Assess       Date:  2019-01-10

2.  Notes on measurement theory for causal-formative indicators: A reply to Hardin.

Authors:  Kenneth A Bollen; Adamantios Diamantopoulos
Journal:  Psychol Methods       Date:  2017-09

3.  Iron deficiency in infancy and neurocognitive and educational outcomes in young adulthood.

Authors:  Patricia East; Jenalee R Doom; Estela Blanco; Raquel Burrows; Betsy Lozoff; Sheila Gahagan
Journal:  Dev Psychol       Date:  2021-06

4.  Symptom Structure in Schizophrenia: Implications of Latent Variable Modeling vs Network Analysis.

Authors:  Samuel J Abplanalp; Michael F Green
Journal:  Schizophr Bull       Date:  2022-05-07       Impact factor: 7.348

5.  Methodological approaches to the analyses of elder abuse screening measures: Application of latent variable measurement modeling to the WC-RAPS.

Authors:  Jeanne A Teresi; Katja Ocepek-Welikson; Mildred Ramirez; Joy Solomon; Daniel Reingold
Journal:  J Elder Abuse Negl       Date:  2018-10-22

6.  Measuring the Unmeasurable : The Psychometrics of Life History Strategy.

Authors:  Stefan L K Gruijters; Bram P I Fleuren
Journal:  Hum Nat       Date:  2018-03

7.  The Fallacy of the Theoretical Meaning of Formative Constructs.

Authors:  Hervé Guyon
Journal:  Front Psychol       Date:  2018-02-15

Review 8.  Developmental cognitive neuroscience using latent change score models: A tutorial and applications.

Authors:  Rogier A Kievit; Andreas M Brandmaier; Gabriel Ziegler; Anne-Laura van Harmelen; Susanne M M de Mooij; Michael Moutoussis; Ian M Goodyer; Ed Bullmore; Peter B Jones; Peter Fonagy; Ulman Lindenberger; Raymond J Dolan
Journal:  Dev Cogn Neurosci       Date:  2017-11-22       Impact factor: 5.811

9.  Comparing alternative methods of measuring cumulative risk based on multiple risk indicators: Are there differential effects on children's externalizing problems?

Authors:  Idean Ettekal; Rina D Eiden; Amanda B Nickerson; Pamela Schuetze
Journal:  PLoS One       Date:  2019-07-03       Impact factor: 3.240

Review 10.  Measurement models for studying child executive functioning: Questioning the status quo.

Authors:  Marie Camerota; Michael T Willoughby; Clancy B Blair
Journal:  Dev Psychol       Date:  2020-10-26
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