World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
42
Citations
17113
World Ranking
1743
National Ranking
748

Andrea Rotnitzky 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 Andrea Rotnitzky 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: 82 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

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

Andrea Rotnitzky 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 Andrea Rotnitzky 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: 42 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Andrea Rotnitzky is affiliated with the University of Washington in the United States and works primarily within the field of mathematics. Their research focuses extensively on statistics and probability, with additional involvement in artificial intelligence, economics and econometrics, experimental and cognitive psychology, and neurology.

The scientist's main areas of study emphasize advanced causal inference techniques and statistical methods. Their work covers a range of topics including:

  • Advanced Causal Inference Techniques
  • Statistical Methods and Inference
  • Statistical Methods in Clinical Trials
  • Statistical Methods and Bayesian Inference
  • Bayesian Modeling and Causal Inference
  • Mental Health Research Topics
  • Long-Term Effects of COVID-19

Andrea Rotnitzky has published in several scientific venues, with a notable presence in:

  • arXiv (Cornell University)
  • Biometrika
  • Journal of Causal Inference
  • Journal of the American Statistical Association
  • Epidemiology

Some of their recent papers include:

  • Characterization of parameters with a mixed bias property, 2020, Biometrika
  • Efficient adjustment sets in causal graphical models with hidden variables, 2021, Biometrika
  • A note on efficient minimum cost adjustment sets in causal graphical models, 2022, Journal of Causal Inference
  • Efficient Estimation of Optimal Regimes Under a No Direct Effect Assumption, 2020, Journal of the American Statistical Association
  • Double-robust and efficient methods for estimating the causal effects of a binary treatment, 2020, arXiv (Cornell University)

The scientist collaborates frequently with researchers who have contributed jointly on multiple occasions. Their frequent coauthors include:

  • Ezequiel Smucler
  • James M. Robins
  • Marco Carone
  • Charles J. Wolock
  • Susan Jacob

Best Publications

  • Estimation of Regression Coefficients When Some Regressors are not Always Observed

    James M. Robins;Andrea Rotnitzky;Lue Ping Zhao

  • Analysis of semiparametric regression models for repeated outcomes in the presence of missing data

    James M. Robins;Andrea Rotnitzky;Lue Ping Zhao

  • The Prevention and Treatment of Missing Data in Clinical Trials

    Roderick J. Little;Ralph D'Agostino;Michael L. Cohen;Kay Dickersin

  • Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models

    Daniel O. Scharfstein;Andrea Rotnitzky;James M. Robins

  • Semiparametric Efficiency in Multivariate Regression Models with Missing Data

    James M. Robins;Andrea Rotnitzky

  • Recovery of Information and Adjustment for Dependent Censoring Using Surrogate Markers

    James M. Robins;Andrea Rotnitzky

  • Semiparametric Regression for Repeated Outcomes With Nonignorable Nonresponse

    Andrea Rotnitzky;James M. Robins;Daniel O. Scharfstein

  • Comment: Performance of Double-Robust Estimators When “Inverse Probability” Weights Are Highly Variable

    James Robins;Mariela Sued;Quanhong Lei-Gomez;Andrea Rotnitzky

  • Sensitivity Analysis for Selection bias and unmeasured Confounding in missing Data and Causal inference models

    James M. Robins;Andrea Rotnitzky;Daniel O. Scharfstein

  • Hypothesis testing of regression parameters in semiparametric generalized linear models for cluster correlated data

    Andrea Rotnitzky;Nicholas P. Jewell

  • Regression Models for Discrete Longitudinal Responses

    Garrett M. Fitzmaurice;Nan M. Laird;Andrea G. Rotnitzky

  • Estimation and extrapolation of optimal treatment and testing strategies.

    James Robins;Liliana Orellana;Andrea Rotnitzky;Andrea Rotnitzky

  • Semiparametric regression estimation in the presence of dependent censoring

    Andrea Rotnitzky;James M. Robins

  • Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: main content.

    Liliana Orellana;Andrea Rotnitzky;James M. Robins

  • Analysis of semi-parametric regression models with non-ignorable non-response.

    Andrea Rotnitzky;James Robins

  • Likelihood-based inference with singular information matrix

    Andrea Rotnitzky;David R. Cox;Matteo Bottai;James Robins

  • Improved double-robust estimation in missing data and causal inference models

    Andrea Rotnitzky;Quanhong Lei;Mariela Sued;James M. Robins

  • Lead and hypertension in a sample of middle-aged women.

    S A Korrick;D J Hunter;A Rotnitzky;H Hu

  • Estimation of treatment effects in randomised trials with non-compliance and a dichotomous outcome using structural mean models

    James Robins;Andrea Rotnitzky

  • Can physical activity minimize weight gain in women after smoking cessation

    Ichiro Kawachi;Rebecca J. Troisi;Andrea G. Rotnitzky;Eugenie H. Coakley

  • Hypothesis Testing of Regression Parameters in Semi-Parametric Generalized Linear Models for Cluster Correlated Data

    Andrea Rotnitzky;Nicholas P. Jewell

Frequent Co-Authors

James M. Robins
James M. Robins Harvard University
Howard Hu
Howard Hu University of Southern California
Scott T. Weiss
Scott T. Weiss Harvard University
David Sparrow
David Sparrow Boston University
Peter B. Gilbert
Peter B. Gilbert Fred Hutchinson Cancer Research Center
Susan A. Korrick
Susan A. Korrick Harvard University
Garrett M. Fitzmaurice
Garrett M. Fitzmaurice Harvard University
Xihong Lin
Xihong Lin Harvard University
Constantine Frangakis
Constantine Frangakis Johns Hopkins University
John D. Spengler
John D. Spengler Harvard University

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