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Mathematics
USA
2026

D-Index & Metrics

Mathematics

D-Index
74
Citations
29145
World Ranking
212
National Ranking
122

Margaret S. Pepe 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 Margaret S. Pepe 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: 145 publications — 35th percentile

35% of scientists in this discipline score the same or lower.

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

Margaret S. Pepe 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 Margaret S. Pepe 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: 74 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Mathematics in United States Leader Award

Overview

Margaret S. Pepe is affiliated with the Fred Hutchinson Cancer Research Center in the United States. The center is known for its contributions to cancer research, and professionals associated with it often focus on epidemiology, biostatistics, and clinical investigation.

Despite the absence of specific records on published papers, co-authors, or detailed research topics, the association with this institution suggests involvement in cancer-related studies, likely with a focus on translating research findings into clinical applications.

There is no available data on frequent publication venues, book publications, fields of study, or specific topics tied to Margaret S. Pepe, which limits the ability to elaborate on particular research interests or thematic areas.

No awards or recognitions have been recorded, and there is no indication of the scientist being deceased, so all references are in present tense.

Best Publications

  • Time-Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker

    Patrick J. Heagerty;Thomas Lumley;Margaret S. Pepe

  • Continual reassessment method: a practical design for phase 1 clinical trials in cancer.

    John O'Quigley;Margaret Pepe;Lloyd Fisher

  • Phases of Biomarker Development for Early Detection of Cancer

    Margaret Sullivan Pepe;Ruth Etzioni;Ziding Feng;John D. Potter

  • Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic, Prognostic, or Screening Marker

    Margaret Sullivan Pepe;Holly Janes;Gary Longton;Wendy Leisenring

  • Kaplan—meier, marginal or conditional probability curves in summarizing competing risks failure time data?

    Margaret Sullivan Pepe;Motomi Mori

  • Pivotal Evaluation of the Accuracy of a Biomarker Used for Classification or Prediction: Standards for Study Design

    Margaret S. Pepe;Ziding Feng;Holly Janes;Patrick M. Bossuyt

  • A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data

    Margaret Sullivan Pepe;Garnet L Anderson

  • Net Reclassification Indices for Evaluating Risk Prediction Instruments: A Critical Review

    Kathleen F. Kerr;Zheyu Wang;Holly Janes;Robyn L. McClelland

  • Comparisons of Predictive Values of Binary Medical Diagnostic Tests for Paired Designs

    Wendy Leisenring;Wendy Leisenring;Todd Alono;Todd Alono;Margaret Sullivan Pepe;Margaret Sullivan Pepe

  • Partial AUC estimation and regression.

    Lori E. Dodd;Margaret S. Pepe

  • Pathologists’ diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study

    Joann G Elmore;Raymond L Barnhill;David E Elder;Gary M Longton

  • Gender Gap in Cystic Fibrosis Mortality

    Margaret Rosenfeld;Robert Davis;Stacey FitzSimmons;Margaret Pepe

  • Combining diagnostic test results to increase accuracy.

    Margaret Sullivan Pepe;Mary Lou Thompson

  • Weighted Kaplan-Meier statistics: a class of distance tests for censored survival data.

    Margaret Sullivan Pepe;Thomas R. Fleming

  • Some Graphical Displays and Marginal Regression Analyses for Recurrent Failure Times and Time Dependent Covariates

    Margaret Sullivan Pepe;Jianwen Cai

  • Estimation and Comparison of Receiver Operating Characteristic Curves

    Margaret S. Pepe;Gary M. Longton;Holly Janes

  • Combining Predictors for Classification Using the Area under the Receiver Operating Characteristic Curve

    Margaret Sullivan Pepe;Margaret Sullivan Pepe;Tianxi Cai;Gary Longton

  • Combining several screening tests: optimality of the risk score.

    Martin W. McIntosh;Margaret Sullivan Pepe;Margaret Sullivan Pepe

  • A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection.

    Yutaka Yasui;Margaret S. Pepe;Mary Lou Thompson;Bao-Ling Adam

  • Integrating the Predictiveness of a Marker with Its Performance as a Classifier

    Margaret S. Pepe;Margaret S. Pepe;Ziding Feng;Ying Huang;Gary M. Longton

  • A mean score method for missing and auxiliary covariate data in regression models

    Marie Reilly;Margaret Sullivan Pepe

  • An Interpretation for the ROC Curve and Inference Using GLM Procedures

    Margaret Sullivan Pepe

  • Inference for Events with Dependent Risks in Multiple Endpoint Studies

    Margaret Sullivan Pepe

  • Assessing the Value of Risk Predictions by Using Risk Stratification Tables

    Holly Janes;Margaret S. Pepe;Wen Gu

Frequent Co-Authors

Ziding Feng
Ziding Feng Fred Hutchinson Cancer Research Center
Joann G. Elmore
Joann G. Elmore University of California, Los Angeles
Rainer Storb
Rainer Storb Fred Hutchinson Cancer Research Center
Todd A. Alonzo
Todd A. Alonzo University of Southern California
Claudio Anasetti
Claudio Anasetti Fred Hutchinson Cancer Research Center
Wendy Leisenring
Wendy Leisenring Fred Hutchinson Cancer Research Center
Anna N. A. Tosteson
Anna N. A. Tosteson Dartmouth College
Christopher I. Li
Christopher I. Li Fred Hutchinson Cancer Research Center
Robert P. Witherspoon
Robert P. Witherspoon Fred Hutchinson Cancer Research Center
Keith M. Sullivan
Keith M. Sullivan Duke University

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