Dexin Shi
Dexin Shi
Assistant Professor of Quantitative Psychology, University of South Carolina
Verified email at mailbox.sc.edu
Title
Cited by
Cited by
Year
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
1932018
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
792019
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
602018
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
352018
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
332020
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
282018
The impact of partial factorial invariance on cross-group comparisons
D Shi, H Song, MD Lewis
Assessment 26 (7), 1217-1233, 2019
272019
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
272018
Bayesian SEM for specification search problems in testing factorial invariance
D Shi, H Song, X Liao, R Terry, LA Snyder
Multivariate behavioral research 52 (4), 430-444, 2017
222017
Effect sizes of model misfit in structural equation models
A Maydeu-Olivares, D Shi
Methodology, 2017
212017
New evidence on causal relationship between approximate number system (ANS) acuity and arithmetic ability in elementary-school students: a longitudinal cross-lagged analysis
Y He, X Zhou, D Shi, H Song, H Zhang, J Shi
Frontiers in psychology 7, 1052, 2016
192016
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
172019
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
162020
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
162020
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
112020
The effect of estimation methods on SEM fit indices
D Shi, A Maydeu-Olivares
Educational and Psychological Measurement 80 (3), 421-445, 2020
102020
Evaluating factorial invariance: An interval estimation approach using Bayesian structural equation modeling
D Shi, H Song, C DiStefano, A Maydeu-Olivares, HL McDaniel, Z Jiang
Multivariate behavioral research 54 (2), 224-245, 2019
92019
Revisiting the model size effect in structural equation modeling (SEM)
D Shi, T Lee, RA Terry
Multivariate Behavioral Research 50 (1), 142-142, 2015
92015
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, 1-13, 2020
62020
Instrumental variable regression: A mean and covariance structure approach
A Maydeu-Olivares, Y Rosseel, D Shi
Manuscript submitted for publication, 2019
62019
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