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Condition 9 and 10 Tests of Model Confirmation: A Review of James, Mulaik, and Brett (1982) and Contemporary Alternatives
Author(s) -
Williams Larry J.,
O’Boyle Ernest H.,
Yu Jia Joya
Publication year - 2020
Publication title -
organizational research methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.901
H-Index - 111
eISSN - 1552-7425
pISSN - 1094-4281
DOI - 10.1177/1094428117736137
Subject(s) - structural equation modeling , latent variable , path analysis (statistics) , confirmatory factor analysis , causal model , econometrics , inference , causal inference , psychology , test (biology) , epistemology , latent variable model , positive economics , computer science , cognitive psychology , sociology , artificial intelligence , statistics , mathematics , economics , philosophy , machine learning , paleontology , biology
Structural equation modeling (SEM) serves as one of the most important advances in the social sciences in the past 40 years. Through a combination of factor analysis and path analysis, SEM allows organizational researchers to test causal models while accounting for random and nonrandom (bias) measurement error. SEM is now one of the most commonly used analytic techniques and its modern day ubiquity can be traced in large part to a series of intellectual contributions by Larry James. The current article focuses on the seminal work, James, Mulaik, and Brett (1982), and the unique contribution of the “conditions” required for appropriate confirmatory inference with the path and latent variable models. We discuss the importance of James et al.’s Condition 9 and 10 tests, systematically review 14 years of studies using SEM in leading management journals and reanalyze results based on new techniques that extend James et al. (1982), and conclude with suggestions for improved Condition 9 and 10 assessments.

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