Causal Interpretations of Psychological Attributes

Autor/in	Kane, Mike
Titel	Causal Interpretations of Psychological Attributes
Quelle	In: Measurement: Interdisciplinary Research and Perspectives, 15 (2017) 2, S.79-82 (4 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1536-6367
DOI	10.1080/15366367.2017.1369771
Schlagwörter	Stellungnahme; Surveys; Validity; Psychological Characteristics; Methods; Measurement Techniques; Causal Models; Theories + Suchen Sie Ihr Suchwort? Survey; Umfrage; Befragung; Gültigkeit; Method; Methode; Messtechnik; Kausalanalyse; Theory; Theorie
Abstract	In the article "Rethinking Traditional Methods of Survey Validation" Andrew Maul describes a minimalist validation methodology for survey instruments, which he suggests is widely used in some areas of psychology and then critiques this methodology empirically and conceptually. He provides a reduction ad absurdum argument by showing that the specified methodology can lead to absurd results and, therefore, cannot be depended on to yield sensible results. He does a nice job of pointing out the limitations of this methodology. Maul concludes that "affairs might be improved via greater attention to definitional clarity and the a priori articulation of testable theories." In this commentary, the author agrees with this suggestion in those cases in which such theories can be articulated. More generally, a testable interpretation/use argument (IUA) can be taken as a testable theory (e.g., see Kane, 2013), and if one had a strong theory for an attribute, that theory could form the heart of the IUA. Most attributes in the social sciences are not embedded in such strong theories and, therefore, the IUA would be looser and more open ended but it could be articulated a priori and it would have testable assumptions. In his conclusions, Maul suggests that researchers should view "claims regarding the existence, measurability, and causal efficacy of psychological attributes as hypotheses" and that they should "work in each situation to construct contextually appropriate theory-based explanations for the processes causing variation in item responses." The author of this commentary is not optimistic about this as a very workable methodology for a variety of reasons, which are outlined in this article. This author makes a few brief remarks about Maul's empirical examples. He then addresses what he considers a major stumbling block in the more ambitious program mentioned in Maul's concluding remarks, the problem of causality. [For "Rethinking Traditional Methods of Survey Validation," see EJ1156001.] (ERIC).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01