World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
50
Citations
12558
World Ranking
1066
National Ranking
497

Ke-Hai Yuan publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Ke-Hai Yuan sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 163 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Ke-Hai Yuan D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Ke-Hai Yuan sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 50 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Ke-Hai Yuan is affiliated with the University of Notre Dame in the United States. Their primary research focus lies within the field of Mathematics, with significant contributions to Statistics and Probability. Their work also spans Management Science and Operations Research, Computer Networks and Communications, as well as Social Psychology and Experimental and Cognitive Psychology.

Their main topics of research include:

  • Psychometric Methodologies and Testing
  • Advanced Statistical Modeling Techniques
  • Advanced Statistical Methods and Models
  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Sensory Analysis and Statistical Methods
  • Advanced Causal Inference Techniques

Ke-Hai Yuan has published extensively in various academic journals. The most frequent venues for their publications are:

  • Structural Equation Modeling A Multidisciplinary Journal
  • Psychological Methods
  • British Journal of Mathematical and Statistical Psychology
  • Personality and Individual Differences
  • Behavior Research Methods

Their recent papers include:

  • "Callous-Unemotional traits and cyberbullying perpetration: The mediating role of moral disengagement and the moderating role of empathy" (2020), Personality and Individual Differences
  • "Effects of Cross-loadings on Determining the Number of Factors to Retain" (2020), Structural Equation Modeling A Multidisciplinary Journal
  • "Childhood psychological maltreatment and moral disengagement: A moderated mediation model of callous-unemotional traits and empathy" (2020), Personality and Individual Differences
  • "Which method is more powerful in testing the relationship of theoretical constructs? A meta comparison of structural equation modeling and path analysis with weighted composites" (2022), Behavior Research Methods
  • "New measures of effect size in moderation analysis." (2020), Psychological Methods

Ke-Hai Yuan collaborates regularly with several coauthors, including:

  • Hongyun Liu
  • Brenna Gomer
  • Katerina M. Marcoulides
  • Zhonglin Wen
  • Lifang Deng

Best Publications

  • Three Likelihood-Based Methods For Mean and Covariance Structure Analysis With Nonnormal Missing Data

    Ke-Hai Yuan;Peter M. Bentler

  • Univariate and multivariate skewness and kurtosis for measuring nonnormality: Prevalence, influence and estimation

    Meghan K. Cain;Zhiyong Zhang;Ke-Hai Yuan

  • Structural Equation Modeling with Small Samples: Test Statistics.

    Peter M. Bentler;Ke-Hai Yuan

  • Fit Indices Versus Test Statistics

    Ke-Hai Yuan

  • Normal theory based test statistics in structural equation modelling

    Ke-Hai Yuan;Peter M. Bentler

  • On Chi-Square Difference and z Tests in Mean and Covariance Structure Analysis when the Base Model is Misspecified:

    Ke-Hai Yuan;Peter M. Bentler

  • Mean and Covariance Structure Analysis: Theoretical and Practical Improvements

    Ke-Hai Yuan;Peter M. Bentler

  • The Effect of Skewness and Kurtosis on Mean and Covariance Structure Analysis The Univariate Case and Its Multivariate Implication

    Ke-Hai Yuan;Peter M. Bentler;Wei Zhang

  • Assessing Structural Equation Models by Equivalence Testing With Adjusted Fit Indexes

    Ke-Hai Yuan;Wai Chan;George A. Marcoulides;Peter M. Bentler

  • On the post hoc power in testing mean differences

    Ke-Hai Yuan;Scott Maxwell

  • Robust Coefficients Alpha and Omega and Confidence Intervals With Outlying Observations and Missing Data Methods and Software

    Zhiyong Zhang;Ke-Hai Yuan

  • On Averaging Variables in a Confirmatory Factor Analysis Model

    Ke-Hai Yuan;Peter M. Bentler;Yutaka Kano

  • Bootstrap approach to inference and power analysis based on three test statistics for covariance structure models

    Ke-Hai Yuan;Kentaro Hayashi

  • Structural Equation Modeling With Robust Covariances

    Ke-Hai Yuan;Peter M. Bentler

  • Measurement invariance via multigroup SEM: Issues and solutions with chi-square-difference tests.

    Ke-Hai Yuan;Wai Chan

  • 10 Structural Equation Modeling

    Ke-Hai Yuan;Peter M. Bentler

  • Robust mean and covariance structure analysis.

    Ke-Hai Yuan;Peter M. Bentler

  • Robust transformation with applications to structural equation modelling.

    Ke-Hai Yuan;Wai Chan;Peter M. Bentler

  • New Ways to Evaluate Goodness of Fit: A Note on Using Equivalence Testing to Assess Structural Equation Models

    Katerina M. Marcoulides;Ke Hai Yuan

  • ML Versus MI for Missing Data With Violation of Distribution Conditions

    Ke-Hai Yuan;Fan Yang-Wallentin;Peter M. Bentler

  • Asymptotics of Estimating Equations under Natural Conditions

    Ke-Hai Yuan;Robert I. Jennrich

Frequent Co-Authors

Peter M. Bentler
Peter M. Bentler University of California, Los Angeles
Kai-Tai Fang
Kai-Tai Fang Beijing Normal University
Scott E. Maxwell
Scott E. Maxwell University of Notre Dame
Bert Hayslip
Bert Hayslip University of North Texas
George A. Marcoulides
George A. Marcoulides University of California, Santa Barbara
Kit-Tai Hau
Kit-Tai Hau Chinese University of Hong Kong
Brad J. Bushman
Brad J. Bushman The Ohio State University
Chrystyna D. Kouros
Chrystyna D. Kouros Southern Methodist University
Steven P. Reise
Steven P. Reise University of California, Los Angeles
Robert I. Jennrich
Robert I. Jennrich University of California, Los Angeles

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Related Online Degrees & Career Pathways

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Moreover, many students seek the easiest MBA program options to combine convenience and career advancement without compromising educational quality. Overall, these pathways complement a background in Mathematics by integrating analytical skillsets with business leadership and decision-making.

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