Melissa Gordon Wolf
Dados Biográficos
| ID | 9095018 |
|---|---|
| NOME | Melissa Gordon Wolf |
| PRENOMES | Melissa Gordon |
| SOBRENOME | Wolf |
| ASSINATURA | WOLF M G |
| AFILIAÇÕES | University of California, Santa Barbara |
| ORCID | 0000-0001-7677-0659 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 4 |
| TOTAL DE CITAÇÕES | 0 |
| OBRAS COMO AUTOR | 4 |
| OBRAS COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2020 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2024 |
| ÍNDICE H | 0 |
Direct Discrepancy Dynamic Fit Index Cutoffs for Arbitrary Covariance Structure Models
Despite the popularity of traditional fit index cutoffs like RMSEA ≤ .06 and CFI ≥ .95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been proposed to avoid overgeneralization by deriving cutoffs specifically tailored to the characteristics of the model being evaluated. Simulations show favorable performance of these methods; however, these methods support a narrow set of scenarios (e.g., …
Dynamic fit index cutoffs for confirmatory factor analysis models.
cutoffs such that derivation of cutoffs is adaptively tailored to the specific model and data characteristics being evaluated. Unlike previously proposed simulation-based techniques, our method removes existing barriers to implementation by providing an open-source, Web based Shiny software application that automates the entire process so that users neither need to manually write any software code nor be knowledgeable about foundations of Monte C…
Dynamic
To evaluate the fit of a confirmatory factor analysis model, researchers often rely on fit indices such as SRMR, RMSEA, and CFI. These indices are frequently compared to benchmark values of .08, .06, and .96, respectively, established by Hu and Bentler (Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55). However, these indices are affected by m…
Thinking twice about sum scores
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Thinking twice about sum scores
Dynamic fit index cutoffs for confirmatory factor analysis models.
cutoffs such that derivation of cutoffs is adaptively tailored to the specific model and data characteristics being evaluated. Unlike previously proposed simulation-based techniques, our method removes existing barriers to implementation by providing an open-source, Web based Shiny software application that automates the entire process so that users neither need to manually write any software code nor be knowledgeable about foundations of Monte C…
Dynamic
To evaluate the fit of a confirmatory factor analysis model, researchers often rely on fit indices such as SRMR, RMSEA, and CFI. These indices are frequently compared to benchmark values of .08, .06, and .96, respectively, established by Hu and Bentler (Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55). However, these indices are affected by m…
Direct Discrepancy Dynamic Fit Index Cutoffs for Arbitrary Covariance Structure Models
Despite the popularity of traditional fit index cutoffs like RMSEA ≤ .06 and CFI ≥ .95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been proposed to avoid overgeneralization by deriving cutoffs specifically tailored to the characteristics of the model being evaluated. Simulations show favorable performance of these methods; however, these methods support a narrow set of scenarios (e.g., …
Computer Science (4 obras) · Econometrics (4 obras) · Machine learning (4 obras) · Mathematics (4 obras) · Statistics (4 obras) · Data mining (3 obras) · Psychometric Methodologies and Testing (3 obras) · Structural equation modeling (3 obras) · Advanced Statistical Modeling Techniques (2 obras) · Algorithm (2 obras)