Abstract

As the use of structural equation modeling (SEM) has increased, confusion has grown concerning the correct use of and the conclusions that can be legitimately drawn from these methodologies. It appears that much of the controversy surrounding SEM is related to the degree of certainty with which causal statements can be drawn from these procedures. SEM is discussed in relation to the conditions necessary for providing causal evidence. Both the weaknesses and the strengths of SEM are examined. Although structural modeling cannot ensure that necessary causal conditions have been met, it is argued that SEM methods may offer the potential for tentative causal inferences to be drawn when used with carefully specified and controlled designs. Keeping in mind that no statistical methodology can in and of itself determine causality, specific guidelines are suggested to help researchers approach a potential for providing causal evidence with SEM procedures. © 1994, Lawrence Erlbaum Associates, Inc.

Keywords

CausationStructural equation modelingCausality (physics)Causal modelCausal inferenceConfusionCausal analysisCertaintyManagement scienceRelation (database)Strengths and weaknessesComputer sciencePsychologyEconometricsEpistemologySocial psychologyMathematicsEngineeringData miningStatisticsPhilosophy

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Year
1994
Type
article
Volume
1
Issue
3
Pages
253-267
Citations
232
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Closed

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Heather E. Bullock, Lisa L. Harlow, Stanley A. Mulaik (1994). Causation issues in structural equation modeling research. Structural Equation Modeling A Multidisciplinary Journal , 1 (3) , 253-267. https://doi.org/10.1080/10705519409539977

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DOI
10.1080/10705519409539977