| 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 | 1177 | 2019 |
| 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 | 540 | 2018 |
| The effect of estimation methods on SEM fit indices D Shi, A Maydeu-Olivares Educational and psychological measurement 80 (3), 421-445, 2020 | 474 | 2020 |
| 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 | 455 | 2020 |
| 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 | 368 | 2021 |
| 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 | 316 | 2021 |
| 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 | 268 | 2018 |
| 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 | 235 | 2022 |
| 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 | 206 | 2018 |
| 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 | 173 | 2022 |
| 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 | 138 | 2021 |
| 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 | 121 | 2021 |
| 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 | 112 | 2018 |
| 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 | 104 | 2019 |
| 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 | 96 | 2019 |
| Chi-square difference tests for comparing nested models: An evaluation with non-normal data G Pavlov, D Shi, A Maydeu-Olivares Structural Equation Modeling: A Multidisciplinary Journal 27 (6), 908-917, 2020 | 95 | 2020 |
| 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 | 95 | 2020 |
| 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 | 93 | 2020 |
| 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 | 93 | 2018 |
| 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 | 91 | 2020 |
Alberto Maydeu-OlivaresProfessor. Psychology Dept. University of South CarolinaVerified email at sc.edu
