Estimating, testing, and comparing specific effects in structural equation models
The phantom model approach.
Bibliographic Data
| ID | 23328893 |
|---|---|
| Authors | Siegfried Macho (0000-0002-3734-2608, University of Fribourg), Thomas Ledermann (0000-0002-4976-6942, University of Connecticut) |
| Year | 2011 |
| Volume | 16 |
| Issue | 1 |
| Pages | 34-43 |
| Publication date | 2011-01-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Psychological Methods (JOURNAL) |
| Journal identifiers | ISSN: 1082-989X • E-ISSN: 1939-1463 |
| Publisher | American Psychological Association (APA) (PUBLISHER) |
| DOI | 10.1037/a0021763 |
| PMID | 21299303 |
| OpenAlex | W2083825606 |
| Language | EN |
| Citations received | 96 |
| References cited | 10 |
The phantom model approach for estimating, testing, and comparing specific effects within structural equation models (SEMs) is presented. The rationale underlying this novel method consists in representing the specific effect to be assessed as a total effect within a separate latent variable model, the phantom model that is added to the main model. The following favorable features characterize the method: (a) It enables the estimation, testing, and comparison of arbitrary specific effects for recursive and nonrecursive models with latent and manifest variables; (b) it enables the bootstrapping of confidence intervals; and (c) it can be applied with all standard SEM programs permitting latent variables, the specification of equality constraints, and the bootstrapping of total effects. These features along with the fact that no manipulation of matrices and formulas is required make the approach particularly suitable for applied researchers. The method is illustrated by means of 3 examples with real data sets.
Algorithm · Bootstrapping (finance) · Econometrics · Imaging phantom · Latent variable · Latent variable model · Statistical hypothesis testing · Statistics · Structural equation modeling · Variable (mathematics) · Applied Mathematics · Artificial Intelligence · Behavioral Health and Interventions · Computer Science · Mathematics · Psychometric Methodologies and Testing
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| Unique citing works | 96 |
|---|---|
| Citations per year | 6,4 |
| Citation span | 2011 - 2026 (16) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 87 |