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Dexin Shi
Dexin Shi
Associate Professor of Quantitative Psychology, University of South Carolina
Verified email at mailbox.sc.edu
Title
Cited by
Cited by
Year
Understanding the model size effect on SEM fit indices
D Shi, T Lee, A Maydeu-Olivares
Educational and psychological measurement 79 (2), 310-334, 2019
6792019
Examination of the weighted root mean square residual: Evidence for trustworthiness?
C DiStefano, J Liu, N Jiang, D Shi
Structural Equation Modeling: A Multidisciplinary Journal 25 (3), 453-466, 2018
4212018
Assessing fit in ordinal factor analysis models: SRMR vs. RMSEA
D Shi, A Maydeu-Olivares, Y Rosseel
Structural Equation Modeling: A Multidisciplinary Journal 27 (1), 1-15, 2020
2532020
The effect of estimation methods on SEM fit indices
D Shi, A Maydeu-Olivares
Educational and psychological measurement 80 (3), 421-445, 2020
2082020
Assessing fit in structural equation models: A Monte-Carlo evaluation of RMSEA versus SRMR confidence intervals and tests of close fit
A Maydeu-Olivares, D Shi, Y Rosseel
Structural Equation Modeling: A Multidisciplinary Journal 25 (3), 389-402, 2018
1712018
A comparison of full information maximum likelihood and multiple imputation in structural equation modeling with missing data.
T Lee, D Shi
Psychological Methods 26 (4), 466, 2021
1572021
Using the standardized root mean squared residual (SRMR) to assess exact fit in structural equation models
G Pavlov, A Maydeu-Olivares, D Shi
Educational and Psychological Measurement 81 (1), 110-130, 2021
1372021
The relationship between the standardized root mean square residual and model misspecification in factor analysis models
D Shi, A Maydeu-Olivares, C DiStefano
Multivariate Behavioral Research 53 (5), 676-694, 2018
1242018
Evaluating SEM model fit with small degrees of freedom
D Shi, C DiStefano, A Maydeu-Olivares, T Lee
Multivariate behavioral research 57 (2-3), 179-207, 2022
862022
Examining chi-square test statistics under conditions of large model size and ordinal data
D Shi, C DiStefano, HL McDaniel, Z Jiang
Structural Equation Modeling: A Multidisciplinary Journal 25 (6), 924-945, 2018
772018
Collapsing categories is often more advantageous than modeling sparse data: Investigations in the CFA framework
C DiStefano, D Shi, GB Morgan
Structural Equation Modeling: A Multidisciplinary Journal 28 (2), 237-249, 2021
732021
Fitting ordinal factor analysis models with missing data: A comparison between pairwise deletion and multiple imputation
D Shi, T Lee, AJ Fairchild, A Maydeu-Olivares
Educational and Psychological Measurement 80 (1), 41-66, 2020
712020
Revisiting the model size effect in structural equation modeling
D Shi, T Lee, RA Terry
Structural Equation Modeling: A Multidisciplinary Journal 25 (1), 21-40, 2018
692018
The impact of partial factorial invariance on cross-group comparisons
D Shi, H Song, MD Lewis
Assessment 26 (7), 1217-1233, 2019
602019
Estimating causal effects in linear regression models with observational data: The instrumental variables regression model.
A Maydeu-Olivares, D Shi, AJ Fairchild
Psychological methods 25 (2), 243, 2020
572020
Fitting latent growth models with small sample sizes and non-normal missing data
D Shi, C DiStefano, X Zheng, R Liu, Z Jiang
International Journal of Behavioral Development 45 (2), 179-192, 2021
562021
Instrumental variables two-stage least squares (2SLS) vs. maximum likelihood structural equation modeling of causal effects in linear regression models
A Maydeu-Olivares, D Shi, Y Rosseel
Structural Equation Modeling: A Multidisciplinary Journal 26 (6), 876-892, 2019
542019
Estimating the maximum likelihood root mean square error of approximation (RMSEA) with non-normal data: A Monte-Carlo study
C Gao, D Shi, A Maydeu-Olivares
Structural Equation Modeling: A Multidisciplinary Journal 27 (2), 192-201, 2020
502020
Assessing cutoff values of SEM fit indices: Advantages of the unbiased SRMR index and its cutoff criterion based on communality
C Ximénez, A Maydeu-Olivares, D Shi, J Revuelta
Structural Equation Modeling: A Multidisciplinary Journal 29 (3), 368-380, 2022
482022
Fitting large factor analysis models with ordinal data
C DiStefano, HL McDaniel, L Zhang, D Shi, Z Jiang
Educational and Psychological Measurement 79 (3), 417-436, 2019
482019
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