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D-Index & Metrics

Social Sciences and Humanities

D-Index
49
Citations
10110
World Ranking
2940
National Ranking
1427

John M. Ferron publication distribution in Social Sciences and Humanities in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Social Sciences and Humanities in 2026. The highlighted bar marks where John M. Ferron sits on this spectrum.

44–53 publications: 28 scientists 54–63 publications: 61 scientists 64–73 publications: 161 scientists 74–83 publications: 225 scientists 84–93 publications: 301 scientists 94–103 publications: 390 scientists 104–113 publications: 406 scientists 114–123 publications: 474 scientists 124–133 publications: 453 scientists 134–143 publications: 434 scientists 144–153 publications: 407 scientists 154–163 publications: 411 scientists 164–173 publications: 391 scientists 174–183 publications: 313 scientists 184–193 publications: 319 scientists 194–203 publications: 304 scientists 204–213 publications: 285 scientists 214–223 publications: 246 scientists 224–233 publications: 213 scientists 234–243 publications: 170 scientists 244–253 publications: 167 scientists 254–263 publications: 162 scientists 264–273 publications: 138 scientists 274–283 publications: 138 scientists 284–293 publications: 113 scientists 294–303 publications: 106 scientists 304–313 publications: 95 scientists 314–323 publications: 101 scientists 324–333 publications: 81 scientists 334–343 publications: 69 scientists 344–353 publications: 56 scientists 354–363 publications: 36 scientists 364–373 publications: 42 scientists 374–383 publications: 41 scientists 384–393 publications: 44 scientists 394–403 publications: 27 scientists 404–413 publications: 30 scientists 414–423 publications: 20 scientists 424–433 publications: 29 scientists 434–443 publications: 29 scientists 444–453 publications: 25 scientists 454–463 publications: 19 scientists 464–473 publications: 21 scientists 474–483 publications: 11 scientists 484–493 publications: 17 scientists 494–503 publications: 7 scientists 504–513 publications: 6 scientists 514–523 publications: 12 scientists 524–533 publications: 10 scientists 534–543 publications: 7 scientists 544–553 publications: 6 scientists 554–563 publications: 12 scientists 564–569 publications: 8 scientists 570+ publications: 100 scientists
44 publications 570+

This scientist: 177 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 570 publications or more.

John M. Ferron D-index placement in Social Sciences and Humanities in 2026

The chart shows the D-index (discipline H-index) distribution of Social Sciences and Humanities scientists ranked by Research.com in 2026. The highlighted bar marks where John M. Ferron sits on this spectrum.

30 D-Index: 177 scientists 31 D-Index: 210 scientists 32 D-Index: 222 scientists 33 D-Index: 188 scientists 34 D-Index: 181 scientists 35 D-Index: 243 scientists 36 D-Index: 261 scientists 37 D-Index: 272 scientists 38 D-Index: 278 scientists 39 D-Index: 300 scientists 40 D-Index: 297 scientists 41 D-Index: 308 scientists 42 D-Index: 313 scientists 43 D-Index: 300 scientists 44 D-Index: 269 scientists 45 D-Index: 260 scientists 46 D-Index: 228 scientists 47 D-Index: 251 scientists 48 D-Index: 203 scientists 49 D-Index: 186 scientists 50 D-Index: 187 scientists 51 D-Index: 166 scientists 52 D-Index: 138 scientists 53 D-Index: 141 scientists 54 D-Index: 131 scientists 55 D-Index: 137 scientists 56 D-Index: 109 scientists 57 D-Index: 129 scientists 58 D-Index: 95 scientists 59 D-Index: 105 scientists 60 D-Index: 106 scientists 61 D-Index: 86 scientists 62 D-Index: 94 scientists 63 D-Index: 77 scientists 64 D-Index: 79 scientists 65 D-Index: 59 scientists 66 D-Index: 68 scientists 67 D-Index: 51 scientists 68 D-Index: 49 scientists 69 D-Index: 40 scientists 70 D-Index: 43 scientists 71 D-Index: 40 scientists 72 D-Index: 50 scientists 73 D-Index: 46 scientists 74 D-Index: 43 scientists 75 D-Index: 45 scientists 76 D-Index: 45 scientists 77 D-Index: 30 scientists 78 D-Index: 25 scientists 79 D-Index: 31 scientists 80 D-Index: 29 scientists 81 D-Index: 18 scientists 82 D-Index: 21 scientists 83 D-Index: 26 scientists 84 D-Index: 15 scientists 85 D-Index: 15 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 12 scientists 89 D-Index: 7 scientists 90 D-Index: 19 scientists 91 D-Index: 20 scientists 92 D-Index: 13 scientists 93 D-Index: 9 scientists 94 D-Index: 13 scientists 95 D-Index: 8 scientists 96 D-Index: 7 scientists 97 D-Index: 6 scientists 98 D-Index: 6 scientists 99 D-Index: 6 scientists 100+ D-Index: 97 scientists
30 D-Index 100+

This scientist: 49 D-Index — 64th percentile

64% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 100 D-Index or more.

Overview

John M. Ferron is affiliated with the University of South Florida in the United States and focuses primarily on research within the field of psychology. Their scholarly work spans several specialized areas including developmental and educational psychology, clinical psychology, cognitive neuroscience, education, and statistics and probability.

Their research addresses a range of topics mainly concentrated on behavioral and psychological studies, autism spectrum disorder research, and child and adolescent psychosocial and emotional development. Other key topics include optimal experimental design methods, early childhood education and development, health policy implementation science, and family and disability support research.

Ferron's publication record includes contributions to multiple academic journals, with frequent appearances in the Journal of School Psychology, Evidence-Based Communication Assessment and Intervention, Perspectives on Behavior Science, Behavior Research Methods, and School Psychology.

Recent papers authored or co-authored by Ferron include:

  • Single-case design standards: An update and proposed upgrades (2021), Journal of School Psychology
  • Single-case intervention research design standards: Additional proposed upgrades and future directions (2023), Journal of School Psychology
  • Indexing effects in single-case experimental designs by estimating the percent of goal obtained (2020), Evidence-Based Communication Assessment and Intervention
  • A systematic review of single-case experimental design meta-analyses: characteristics of study designs, data, and analyses (2022), Evidence-Based Communication Assessment and Intervention
  • Investigation of Single-Case Multiple-Baseline Randomization Tests of Trend and Variability (2020), Educational Psychology Review

Frequent co-authors who have collaborated with Ferron include Mariola Moeyaert, Shannon M. Suldo, Joel R. Levin, S. Natasha Beretvas, and Wim Van Den Noortgate. This collaboration network reflects interdisciplinary and methodological approaches in single-case research designs and applied psychology.

Best Publications

  • The Quality of Factor Solutions in Exploratory Factor Analysis: The Influence of Sample Size, Communality, and Overdetermination.

    Kristine Y. Hogarty;Constance V. Hines;Jeffrey D. Kromrey;John M. Ferron

  • School demographic variables and out-of-school suspension rates: A quantitative and qualitative analysis of a large, ethnically diverse school district

    Linda M. Raffaele Mendez;Howard M. Knoff;John M. Ferron

  • Longitudinal academic outcomes predicted by early adolescents’ subjective well-being, psychopathology, and mental health status yielded from a dual factor model

    Shannon Suldo;Amanda Thalji;John Ferron

  • Poverty Experiences of Young Children and the Quality of Their Home Environments

    Patricia Garrett;Nicholas Ng'andu;John Ferron

  • Emerging Risks of Violence in the Digital Age: Lessons for Educators from an Online Study of Adolescent Girls in the United States.

    Ilene R. Berson;Michael J. Berson;John M. Ferron

  • Multilevel Modeling: A Review of Methodological Issues and Applications

    Robert F. Dedrick;John M. Ferron;Melinda R. Hess;Kristine Y. Hogarty

  • Methods for dealing with multiple outcomes in meta-analysis: a comparison between averaging effect sizes, robust variance estimation and multilevel meta-analysis

    Mariola Moeyaert;Maaike Ugille;S. Natasha Beretvas;John Ferron

  • How Low Can You Go? An Investigation of the Influence of Sample Size and Model Complexity on Point and Interval Estimates in Two-Level Linear Models

    Bethany A. Bell;Grant B. Morgan;Jason A. Schoeneberger;Jeffrey D. Kromrey

  • Making treatment effect inferences from multiple-baseline data: the utility of multilevel modeling approaches.

    John M. Ferron;Bethany A. Bell;Melinda R. Hess;Gianna Rendina-Gobioff

  • Cluster Size in Multilevel Models: The Impact of Sparse Data Structures on Point and Interval Estimates in Two-Level Models

    Bethany A. Bell;John M. Ferron;Jeffrey D. Kromrey

  • From a single-level analysis to a multilevel analysis of single-case experimental designs☆

    Mariola Moeyaert;John M. Ferron;S. Natasha Beretvas;Wim Van den Noortgate

  • The Impact of Small Cluster Size on Multilevel Models: A Monte Carlo Examination of Two-Level Models with Binary and Continuous Predictors

    Bethany A. Bell;Grant B. Morgan;Jeffrey D. Kromrey;John M. Ferron

  • Conceptualizing High School Students' Mental Health through a Dual-Factor Model

    Shannon M. Suldo;Amanda Thalji-Raitano;Sarah M. Kiefer;John M. Ferron

  • Effects of Misspecifying the First-Level Error Structure in Two-Level Models of Change

    John Ferron;Ron Dailey;Qing Yi

  • Tests for the Visual Analysis of Response-Guided Multiple-Baseline Data

    John Ferron;Peggy K. Jones

  • Statistical Power of Randomization Tests Used with Multiple-Baseline Designs

    John Ferron;Chris Sentovich

  • Capacity, strategies, and metamemory: tests of a three-factor model of memory development.

    Darlene DeMarie;John Ferron

  • Multilevel Factor Analysis: Reporting Guidelines and a Review of Reporting Practices.

    Eun Sook Kim;Robert F. Dedrick;Chunhua Cao;John M. Ferron

  • Use of Design Effects and Sample Weights in Complex Health Survey Data: A Review of Published Articles Using Data From 3 Commonly Used Adolescent Health Surveys

    Bethany A. Bell;Anthony J. Onwuegbuzie;John M. Ferron;Qun G. Jiao

  • Estimating individual treatment effects from multiple-baseline data: a Monte Carlo study of multilevel-modeling approaches.

    John M. Ferron;Jennie L. Farmer;Corina M. Owens

Frequent Co-Authors

Shannon M. Suldo
Shannon M. Suldo University of South Florida
Joel R. Levin
Joel R. Levin University of Arizona
Howard Goldstein
Howard Goldstein University of South Florida
Anthony J. Onwuegbuzie
Anthony J. Onwuegbuzie University of Johannesburg
Thomas R. Kratochwill
Thomas R. Kratochwill University of Wisconsin–Madison
Robert H. Horner
Robert H. Horner University of Oregon
Stephen Stark
Stephen Stark University of South Florida
Patricia H. Miller
Patricia H. Miller San Francisco State University

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