Dexin Shi

4.4k total citations · 4 hit papers
71 papers, 2.8k citations indexed

About

Dexin Shi is a scholar working on Management Science and Operations Research, Statistics and Probability and Computer Networks and Communications. According to data from OpenAlex, Dexin Shi has authored 71 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Management Science and Operations Research, 30 papers in Statistics and Probability and 25 papers in Computer Networks and Communications. Recurrent topics in Dexin Shi's work include Psychometric Methodologies and Testing (36 papers), Advanced Statistical Modeling Techniques (25 papers) and Statistical Methods and Bayesian Inference (17 papers). Dexin Shi is often cited by papers focused on Psychometric Methodologies and Testing (36 papers), Advanced Statistical Modeling Techniques (25 papers) and Statistical Methods and Bayesian Inference (17 papers). Dexin Shi collaborates with scholars based in United States, China and Spain. Dexin Shi's co-authors include Alberto Maydeu‐Olivares, Taehun Lee, Christine DiStefano, Yves Rosseel, Jin Liu, Ning Jiang, Taehun Lee, Zhehan Jiang, Amanda J. Fairchild and Robert Terry and has published in prestigious journals such as SHILAP Revista de lepidopterología, Child Development and The Journal of Pediatrics.

In The Last Decade

Dexin Shi

64 papers receiving 2.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Understanding the Model Size Effect on SEM Fit Indices

2018 527 citations Dexin Shi, Taehun Lee et al. Educational and Psychological Measurement profile →
Examination of the Weighted Root Mean Square Residual: Evidence for Trustworthiness?

2017 267 citations Christine DiStefano, Dexin Shi et al. Structural Equation Modeling A Multidisciplinary Journal profile →
Assessing Fit in Ordinal Factor Analysis Models: SRMR vs. RMSEA

2019 232 citations Dexin Shi, Alberto Maydeu‐Olivares et al. Structural Equation Modeling A Multidisciplinary Journal profile →
A comparison of full information maximum likelihood and multiple imputation in structural equation modeling with missing data.

2021 170 citations Taehun Lee, Dexin Shi Psychological Methods profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Dexin Shi United States	23	661	606	401	377	347	71	2.8k
Donna L. Coffman United States	29	656 1.0×	512 0.8×	491 1.2×	360 1.0×	239 0.7×	108	3.1k
Patricia É. Brosseau-Liard Canada	13	660 1.0×	702 1.2×	447 1.1×	479 1.3×	234 0.7×	25	2.5k
W. Holmes Finch United States	33	566 0.9×	623 1.0×	387 1.0×	582 1.5×	432 1.2×	161	3.7k
Zhiyong Zhang United States	27	482 0.7×	452 0.7×	545 1.4×	473 1.3×	336 1.0×	96	3.2k
Thomas A. Schmitt United States	16	822 1.2×	671 1.1×	354 0.9×	360 1.0×	239 0.7×	32	2.4k
Feinian Chen United States	21	558 0.8×	569 0.9×	1.1k 2.8×	381 1.0×	364 1.0×	46	3.4k
Yanyun Yang United States	24	1.1k 1.7×	741 1.2×	479 1.2×	710 1.9×	407 1.2×	68	3.6k
Pui‐Wa Lei United States	28	678 1.0×	506 0.8×	307 0.8×	366 1.0×	245 0.7×	97	3.2k
Felix Thoemmes United States	22	500 0.8×	536 0.9×	509 1.3×	459 1.2×	136 0.4×	49	2.5k

Countries citing papers authored by Dexin Shi

Since Specialization

Citations

This map shows the geographic impact of Dexin Shi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dexin Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dexin Shi more than expected).

Fields of papers citing papers by Dexin Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dexin Shi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dexin Shi. The network helps show where Dexin Shi may publish in the future.

Co-authorship network of co-authors of Dexin Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Dexin Shi. A scholar is included among the top collaborators of Dexin Shi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dexin Shi. Dexin Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Lee, Taehun, et al.. (2025). Research Trends and Challenges in Diagnostic Classification Models: Insights from Dynamic Topic Modeling. Measurement Interdisciplinary Research and Perspectives. 1–32.

Shi, Dexin, Bo Zhang, Wolfgang Wiedermann, & Amanda J. Fairchild. (2025). Distinguishing cause from effect in psychological research: An independence‐based approach under linear non‐Gaussian models. British Journal of Mathematical and Statistical Psychology. 78(3). 965–995.

Fairchild, Amanda J., et al.. (2024). Many nonnormalities, one simulation: Do different data generation algorithms affect study results?. Behavior Research Methods. 56(7). 6464–6484. 3 indexed citations

Wiedermann, Wolfgang, et al.. (2023). Detecting heterogeneity in the causal direction of dependence: A model-based recursive partitioning approach. Behavior Research Methods. 56(4). 2711–2730. 1 indexed citations

Shi, Dingjing, Dexin Shi, & Amanda J. Fairchild. (2023). Variable Selection for Mediators under a Bayesian Mediation Model. Structural Equation Modeling A Multidisciplinary Journal. 30(6). 887–900. 2 indexed citations

Maydeu‐Olivares, Alberto, et al.. (2022). Asymptotic is Better than Bollen-Stine Bootstrapping to Assess Model Fit: The Effect of Model Size on the Chi-Square Statistic. Structural Equation Modeling A Multidisciplinary Journal. 29(5). 731–743. 13 indexed citations

Ximénez, Carmen, Alberto Maydeu‐Olivares, Dexin Shi, & Javier Revuelta. (2022). Assessing Cutoff Values of SEM Fit Indices: Advantages of the Unbiased SRMR Index and Its Cutoff Criterion Based on Communality. Structural Equation Modeling A Multidisciplinary Journal. 29(3). 368–380. 69 indexed citations

Bradshaw, Jessica, et al.. (2022). The Pull-to-Sit Task: Examining Infant Postural Development in Autism Spectrum Disorder. The Journal of Pediatrics. 253. 225–231.e2. 7 indexed citations

Shi, Dexin, et al.. (2021). Item desirability matching in forced-choice test construction. Personality and Individual Differences. 183. 111114–111114. 20 indexed citations

10.

Shi, Dexin, Christine DiStefano, Alberto Maydeu‐Olivares, & Taehun Lee. (2021). Evaluating SEM Model Fit with Small Degrees of Freedom. Multivariate Behavioral Research. 57(2-3). 179–207. 93 indexed citations

11.

Lee, Taehun & Dexin Shi. (2021). A comparison of full information maximum likelihood and multiple imputation in structural equation modeling with missing data.. Psychological Methods. 26(4). 466–485. 170 indexed citations breakdown →

12.

Shi, Dexin, et al.. (2020). Chi-square Difference Tests for Comparing Nested Models: An Evaluation with Non-normal Data. Structural Equation Modeling A Multidisciplinary Journal. 27(6). 908–917. 38 indexed citations

13.

Shi, Dexin, Taehun Lee, Amanda J. Fairchild, & Alberto Maydeu‐Olivares. (2019). Fitting Ordinal Factor Analysis Models With Missing Data: A Comparison Between Pairwise Deletion and Multiple Imputation. Educational and Psychological Measurement. 80(1). 41–66. 51 indexed citations

14.

Maydeu‐Olivares, Alberto, Dexin Shi, & Amanda J. Fairchild. (2019). Estimating causal effects in linear regression models with observational data: The instrumental variables regression model.. Psychological Methods. 25(2). 243–258. 52 indexed citations

15.

Gao, Chuanji, Dexin Shi, & Alberto Maydeu‐Olivares. (2019). Estimating the Maximum Likelihood Root Mean Square Error of Approximation (RMSEA) with Non-normal Data: A Monte-Carlo Study. Structural Equation Modeling A Multidisciplinary Journal. 27(2). 192–201. 46 indexed citations

16.

Maydeu‐Olivares, Alberto, Dexin Shi, & Yves Rosseel. (2019). Instrumental Variables Two-Stage Least Squares (2SLS) vs. Maximum Likelihood Structural Equation Modeling of Causal Effects in Linear Regression Models. Structural Equation Modeling A Multidisciplinary Journal. 26(6). 876–892. 58 indexed citations

17.

Fairchild, Amanda J., et al.. (2019). Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes. Frontiers in Psychology. 10. 740–740. 7 indexed citations

18.

Shi, Dexin, Taehun Lee, & Alberto Maydeu‐Olivares. (2018). Understanding the Model Size Effect on SEM Fit Indices. Educational and Psychological Measurement. 79(2). 310–334. 527 indexed citations breakdown →

19.

Zhou, Xinlin, et al.. (2016). New Evidence on Causal Relationship between Approximate Number System (ANS) Acuity and Arithmetic Ability in Elementary-School Students: A Longitudinal Cross-Lagged Analysis. Frontiers in Psychology. 7. 1052–1052. 17 indexed citations

20.

Shi, Dexin, Taehun Lee, & Robert Terry. (2015). Abstract: Revisiting the Model Size Effect in Structural Equation Modeling (SEM). Multivariate Behavioral Research. 50(1). 142–142. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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