The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions.
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Summary
Results of the Monte Carlo simulation indicated that measurement model misspecification can inflate unstandardized structural parameter estimates by as much as 400% or deflate them by asMuch as 80% and lead to Type I or Type II errors of inference, depending on whether the exogenous or the endogenous latent construct is misspecified.
- Type
- article
- Published
- 2005-07-01
- Cited by
- 1,790
- References
- 50
- Access
- Open access
- OpenAlex
- https://openalex.org/W1988897250
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:27365175
Keywords
Formative assessment, Monte Carlo method, Construct (python library), Structural equation modeling, Inference
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- A Paradigm for Developing Better Measures of Marketing Constructs
- Alternative Ways of Assessing Model Fit
- Overall Fit in Covariance Structure Models: Two Types of Sample Size Effects
- Fit indices in covariance structure modeling : Sensitivity to underparameterized model misspecification
- Some Possible Antecedents and Consequences of In-Role and Extra-Role Salesperson Performance
- Toward a Greater Understanding of How Dissatisfaction Drives Employee Turnover
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