Bio


PERSONAL BACKGROUND:

I grew up in an Italian New Jersey family, and attended Princeton where I was influenced by John Tukey and terrific mentor Nick Jewell. I got my Ph.D. from Berkeley in 1986, where I was fortunate enough to meet many of the great statisticians of the 20th century, including Erich Lehmann, Lucien LeCam, David Freedman, Rudy Beran, and others. I joined the faculty at Stanford in 1986 when I was 25 and have been at Stanford ever since. My professional life combines intellectual advancement, teaching, and mentoring of young students and researchers by sharing of knowledge and promoting academic integrity. I am proud to be part of the 500 Queer Scientists visibility campaign. I also lead a balanced life with passions in music (having performed at Carnegie Hall), tennis (ranked nationally in my age group), cooking, architecture, and other interests.


RESEARCH GOALS:

Statistics is concerned with making sense or inferences about the world based on limited information and uncertainties. In contrast, mathematics is exact, where the goal is to prove theorems based on a well-defined set of assumptions. It is the juxtaposition of statistics and mathematics that I find intriguing and challenging. Mathematical statistics serves to precisely quantify and explain what can be learned from data in spite of having to acknowledge our uncertainty in the process.

While much of my own research has been theoretically oriented, I have been motivated by a desire to develop practical statistical methodology in order to construct techniques that may be applied safely in practice. I have been particularly interested in advancing "nonparametric" techniques that do not rely on the statistician having to invoke unverifiable assumptions. In my work, I have tried to explore the extent of applicability of bootstrap, subsampling, and other resampling methods, as well as understanding their limitations.

In recent years, I have been interested in developing new methods for multiple testing and multivariate inference, especially driven by the availability of massive data sets. For example current methods in biotechnology generate ultra high throughput data, where expression levels in tens of thousands of genes or SNP data with hundreds of thousands of locations must be analyzed simultaneously. Multiple testing methods can be used to understand the hidden structure in the data rather than random artifacts (due to "data snooping"). In addition, the analysis of data is complicated by large number of features with unknown dependence structures, heterogeneity, model fitting, high dimensionality and other unknown sources of variation. The statistician is then faced with the challenge of accounting for all possible errors resulting from a complex data analysis, so that any resulting inferences or interesting conclusions can reliable be viewed as real structure (and is reproducible or has predictive power). Thus, my goals are the development of universal statistical tools that can be applied to such diverse fields as econometrics, climate science, genetics, clinical trials, finance, education, etc. The many burgeoning fields of applications demand new statistical methods, creating exciting opportunities for statisticians and data scientists.

Academic Appointments


Administrative Appointments


  • Assistant Professor, Department of Statistics, Stanford University (1986 - 1994)
  • Associate Professor, Department of Statistics, Stanford University (1994 - 2000)
  • Full Professorship in Statistics, Stanford University (2000 - Present)
  • Joint Professorship, Stanford University (2007 - Present)

Honors & Awards


  • 2021 LGBTQ+ Scientist of the Year, Out to Innovate (National Organization of Gay and Lesbian Scientists and Technical Professionals) (2021)
  • Fellow, International Association of Applied Econometrics (2020)
  • Computer-intensive Inference with Applications to Social Sciences, National Science Foundation Grant (July 2020-June 2023)
  • Randomization Inference for Contemporary Problems in Statistics, National Science Foundation Research Grant (July 2013-June 2016)
  • Multiple Problems in Multiple Testing and Simultaneous Inference, National Science Foundation Research Grant (July 2010 - June 2013)
  • New Methodology for Multiple Testing and Simultaneous Inference, National Science Foundation Research Grant (July 2007 - June 2010)
  • Theory and Methods for Multiple Testing and Inference, National Science Foundation Research Grant (July 2004 - June 2007)
  • Approximate and Exact Inference Via Computer Intensive Methods, National Science Foundation Research Grant (July 2001 - June 2004)
  • Computer-Intensive Methods for the Statistical Analysis of Dependent Data, National Science Foundation Research Grant (September 1997 - August 2000)
  • Fellow, Institute of Mathematical Statistics (2000)
  • Computer Intensive Methods for the Statistical Analysis of Time Series and Random Fields, National Science Foundation Research Grant (September 1994 - August 1997)
  • Presidential Young Investigator Award, National Science Foundation (1989-1994)
  • The Canadian Journal of Statistics Award, Statistical Society of Canada (1989)
  • Postdoctoral Fellowship, National Science Foundation (1986-1988)
  • Graduate Fellowship, National Science Foundation (1982-1984)
  • Collegiate Award, Northern New Jersey Chapter of the American Statistical Association (1982)
  • Graduated Summa Cum Laude in Statistics, Princeton University (1982)
  • Member, Phi Beta Kappa Society (1982)

Boards, Advisory Committees, Professional Organizations


  • Fellow, Institute of Mathematical Statistics
  • Grant Proposal Reviewer, National Security Agency Mathematical Sciences Program
  • Grant Proposal Reviewer, National Science Foundation
  • Grant Proposal Reviewer, Natural Science and Engineering Research Council of Canada
  • Member, American Statistical Association
  • Referee, Algorithmic Learning Theory
  • Referee, Biometrics
  • Referee, Journal of Statistical Planning and Inference
  • Referee, Journal of Statistical Computation and Simulation
  • Referee, The Scandinavian Journal of Statistics
  • Referee, Journal of Econometrics
  • Referee, British Journal of Mathematical and Statistical Psychology
  • Referee, Statistical Science
  • Referee, Biometrika
  • Referee, The American Statistician
  • Referee, Journal of the Italian Statistical Society
  • Referee, Transactions on Signal Processing
  • Referee, Technometrics
  • Referee, Proceedings of the American Mathematical Society
  • Referee, Communications in Statistics
  • Referee, Journal of the American Statistical Association
  • Referee, Bernoulli
  • Referee, Journal of the Royal Statistical Association
  • Referee, The British Journal of Mathematical and Statistical Psychology
  • Referee, Statistica Sinica
  • Referee, Journal of Time Series Analysis
  • Referee, Psychometrika
  • Referee, Annals of Probability
  • Referee, Econometrica
  • Referee, International Statistical Review
  • Referee, Annals of Statistics
  • Referee, Annals of the Institute of Statistical Mathematics
  • Referee, The Canadian Journal of Statistics
  • Referee, The Journal of Nonparametric Statistics
  • Fellow, International Association of Applied Econometrics (2020 - Present)
  • Associate Chairman, Stanford University (2013 - 2014)
  • Chair of Qualifying Exams, Stanford University (2012 - 2013)
  • Master's Advisor, Stanford University (2012 - 2013)
  • Member, Ph.D. Admissions Committee, Stanford University (2011 - 2012)
  • Chair of Qualifying Exams, Stanford University (2010 - 2011)
  • Advisor to Master's Degree Students, Stanford University (2009 - 2010)
  • Advisor to Master's Degree Students, Stanford University (2008 - 2009)
  • Member, Faculty Affairs Committee, Stanford University (2008 - 2009)
  • Chair of Committee on Faculty Affairs, Stanford University (2007 - 2008)
  • Vice Chairman of the Department of Statistics, Stanford University (2007 - 2008)
  • Vice Chairman, Noether Award Committee, American Statistical Association (2007 - 2007)
  • Member, Noether Award Committee, American Statistical Association (2006 - 2011)
  • Associate Editor, The Annals of Applied Statistics (2006 - 2010)
  • Master's Degree Advisor, Stanford University (2006 - 2007)
  • Member, Committee on Faculty Affairs, Stanford University (2006 - 2007)
  • Master's Degree Advisor, Stanford University (2005 - 2006)
  • Member, Ph.D. Admissions Committee, Stanford University (2005 - 2006)
  • Advisor to all students in the Master's Degree and Ph.D. Minor Programs, Stanford University (2004 - 2005)
  • Chair of Qualifying Exam Committee, Stanford University (2004 - 2005)
  • Member, Grant Proposal Panel, National Science Foundation (2004 - 2004)
  • Advisor to all students in the Master's Degree and Ph.D. Minor Programs, Stanford University (2002 - 2004)
  • Associate Editor, The Annals of Statistics (2001 - 2004)
  • Chair of the Qualifying Exam Committee, Stanford University (2001 - 2002)
  • Member, Ph.D. Program Committee, Stanford University (2001 - 2002)
  • Chair of Qualifying Exam Committee, Stanford University (2000 - 2001)
  • Member, Judicial Panel, Stanford University (2000 - 2001)
  • Ph.D. advisor to first and second year Ph.D. students, Stanford University (1999 - 2000)
  • Chair of Qualifying Exam Committee, Stanford University (1998 - 1999)
  • Ph.D. advisor to first and second year Ph.D. students, Stanford University (1998 - 1999)
  • Chair of Student Selection Committee, Stanford University (1997 - 1998)
  • Ph.D. advisor to first and second year Ph.D. students, Stanford University (1997 - 1998)
  • Chair of Contributed Papers, Annual Meeting of the Institute of Mathematical Statistics (1997 - 1997)
  • Associate Editor, The Journal of Statistical Planning and Inference (1996 - 1999)
  • Ph.D. advisor to to first and second year Ph.D. students, Stanford University (1996 - 1997)
  • Advisor to Ph.D students without thesis advisors, Stanford University (1995 - 1996)
  • Member, Search Committee, Stanford University (1995 - 1996)
  • First Year Ph.D. Student Advisor, Stanford University (1994 - 1995)
  • Qualifying Exam Advisor, Stanford University (1994 - 1995)
  • Member, Ph.D. Exam Committee, Stanford University (1993 - 1994)
  • Ph.D. Student Advisor, Stanford University (1992 - 1993)
  • Masters Student Advisor, Stanford University (1991 - 1992)
  • Member, Ph.D. Exam Committee, Stanford University (1991 - 1992)
  • Member, Affirmative Action Committee, Stanford University (1990 - 1991)
  • Member, Ph.D. Exam Committee, Stanford University (1990 - 1991)
  • Masters Student Advisor, Stanford University (1989 - 1990)
  • Member, Ph.D. Exam Committee, Stanford University (1989 - 1990)
  • Ph.D. Student Selection, Stanford University (1989 - 1990)
  • Member, Curriculum Committee, Stanford University (1988 - 1989)
  • Masters Student Advisor, Stanford University (1987 - 1988)
  • Seminar Chairperson, Ph.D. Exam Committee, Stanford University (1986 - 1987)

Professional Education


  • Ph.D., University of California, Berkeley (1986)
  • M.S., University of California, Berkeley (1983)
  • A.B., Princeton University (1982)

Current Research and Scholarly Interests


Work in progress is described under "Projects"

Projects


  • Control of directional errors in fixed sequence multiple testing (with Anjana Grandhi and Wenge Guo)

    submitted for publication

    Location

    Stanford, CA

    For More Information:

  • Testing for differences between random processes in sample-starved regimes (with Bala Rajaratnam and Michael Tsiang)

    Location

    Stanford, CA

  • Randomization tests under an approximate symmetry assumption (with Ivan Canay and Azeem Shaikh)

    Location

    Stanford, CA

    For More Information:

  • Improved weighted least squares inference (with Cyrus DiCiccio and Michael Wolf)

    Location

    CA

  • Analysis of error control in large scale two stage multiple testing (with Wenge Guo)

    Location

    CA

2024-25 Courses


All Publications


  • Covariate adjustment in experiments with matched pairs JOURNAL OF ECONOMETRICS Bai, Y., Jiang, L., Romano, J. P., Shaikh, A. M., Zhang, Y. 2024; 241 (1)
  • The choice-wide behavioral association study: data-driven identification of interpretable behavioral components. bioRxiv : the preprint server for biology Kastner, D. B., Williams, G., Holobetz, C., Romano, J. P., Dayan, P. 2024

    Abstract

    Behavior contains rich structure across many timescales, but there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method-the choice-wide behavioral association study: CBAS-that systematically identifies such behavioral features. CBAS uses powerful, resampling-based, methods of multiple comparisons correction1-3 to identify sequences of actions or choices that either differ significantly between groups or significantly correlate with a covariate of interest. We apply CBAS to different tasks and species (flies4, rats5, and humans6) and find, in all instances, that it provides interpretable information about each behavioral task.

    View details for DOI 10.1101/2024.02.26.582115

    View details for PubMedID 38464037

  • Inference for Ranks with Applications to Mobility across Neighbourhoods and Academic Achievement across Countries REVIEW OF ECONOMIC STUDIES Mogstad, M., Romano, J. P., Shaikh, A. M., Wilhelm, D. 2023
  • A COMMENT ON: "Invidious Comparisons: Ranking and Selection as Compound Decisions" by Jiaying Gu and Roger Koenker ECONOMETRICA Mogstad, M., Romano, J. P., Shaikh, A. M., Wilhelm, D. 2023; 91 (1): 53-60

    View details for DOI 10.3982/ECTA20460

    View details for Web of Science ID 000967592600004

  • Confidence Intervals for Seroprevalence STATISTICAL SCIENCE DiCiccio, T. J., Ritzwoller, D. M., Romano, J. P., Shaikh, A. M. 2022; 37 (3): 306-321

    View details for DOI 10.1214/21-STS844

    View details for Web of Science ID 000851465300002

  • Statistical Uncertainty in the Ranking of Journals and Universities Mogstad, M., Romano, J., Shaikh, A., Wilhelm, D. AMER ECONOMIC ASSOC. 2022: 630-634
  • Permutation testing for dependence in time series JOURNAL OF TIME SERIES ANALYSIS Romano, J. P., Tirlea, M. A. 2022

    View details for DOI 10.1111/jtsa.12638

    View details for Web of Science ID 000746816600001

  • CLT FOR U-STATISTICS WITH GROWING DIMENSION STATISTICA SINICA DiCiccio, C., Romano, J. 2022; 32 (1): 323-344
  • Uncertainty in the Hot Hand Fallacy: Detecting Streaky Alternatives to Random Bernoulli Sequences REVIEW OF ECONOMIC STUDIES Ritzwoller, D. M., Romano, J. P. 2021
  • Inference in Experiments With Matched Pairs JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Bai, Y., Romano, J. P., Shaikh, A. M. 2021
  • The Romano-Wolf multiple-hypothesis correction in Stata STATA JOURNAL Clarke, D., Romano, J. P., Wolf, M. 2020; 20 (4): 812–43
  • Exact tests via multiple data splitting STATISTICS & PROBABILITY LETTERS DiCiccio, C. J., DiCiccio, T. J., Romano, J. P. 2020; 166
  • Permutation testing for dependence in time series Romano, J., Tirlea, M. Stanford Statistics Department. 2020 ; Stanford Statistics Technical Reports (2020-11):
  • Uncertainty in the hot hand fallacy: Tests of randomness against steady alternatives to Bernoulli sequences Ritzwoller, D., Romano, J. Stanford Statistics Technical Report. 2020 (2020-02):
  • Inference for ranks with applications to mobility across neighborhoods and academic achievement across countries Mogstad, M., Romano, J., Shaikh, A., Wilhelm, D. Stanford Statistics Technical Report 2020-03. 2020
  • CLT for U-statistics with growing dimension Statistica Sinica DiCiccio, C., Romano, J. 2020
  • CONTROL OF DIRECTIONAL ERRORS IN FIXED SEQUENCE MULTIPLE TESTING STATISTICA SINICA Grandhi, A., Guo, W., Romano, J. P. 2019; 29 (2): 1047–64
  • Improving weighted least squares inference ECONOMETRICS AND STATISTICS Diciccio, C. J., Romano, J. R., Wolf, M. 2019; 10: 96–119
  • Multiple data splitting for testing. DiCiccio, C., Romano, J. Stanford. 2019 ; Stanford Statistics Department Techincal Report (2019-3):
  • Inference in experiments with matched pairs Bai, Y., Romano, J., Shaikh, A. Stanford. 2019 ; Stanford University Statistics Department (2019-4):
  • A new approach for large scale multiple testing with application to FDR control of graphically structured hypotheses Guo, W., Lynch, G., Romano, J. Stanford University. 2018 ; Stanford Statistics Department (2018-6):
  • Resurrecting weighted least squares JOURNAL OF ECONOMETRICS Romano, J. P., Wolf, M. 2017; 197 (1): 1-19
  • Improving weighted least squares inference DiCiccio, C., Romano, J., Wolf, M. Department of Statistics, Stanford University. 2017 ; Technical Report (2017-04):
  • Robust Permutation Tests For Correlation And Regression Coefficients JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION DiCiccio, C. J., Romano, J. P. 2017; 112 (519): 1211–20
  • Analysis of error control in large scale two-stage multiple testing Guo, W., Romano, J. Department of Statistics, Stanford University. 2017 ; Technical Report (2017-03):
  • Multiple testing of one-sided hypotheses: combining Bonferroni and the bootstrap Romano, J., Wolf, M. University of Zurich. 2017 ; Working Paper ECON 254
  • Supplement to Approximation randomization tests under an approximate symmetry assumption Econometrica Ivan, C., Joseph, R., Azeem, S. 2017

    View details for DOI 10.3982/ECTA12974

  • Randomization tests under an approximate symmetry assumption Econometrica Ivan, C., Joseph, R., Azeem, S. 2017; 85: 1013-1030
  • Supplement to "Robust permutation tests for correlation and regression coefficients" Robust permutation tests for correlation and regression coefficients DiCiccio, C., Romano, J. 2017
  • Multivariate and multiple permutation tests JOURNAL OF ECONOMETRICS Chung, E., Romano, J. P. 2016; 193 (1): 76-91
  • Efficient computation of adjusted p-values for resampling-based stepdown multiple testing STATISTICS & PROBABILITY LETTERS Romano, J. P., Wolf, M. 2016; 113: 38-40
  • Asymptotically valid and exact permutation tests based on two-sample U-statistics JOURNAL OF STATISTICAL PLANNING AND INFERENCE Chung, E., Romano, J. P. 2016; 168: 97-105
  • Resurrecting weighted least squares Journal of Econometrics Romano, J. P., Michael, W. 2016: to appear
  • Debunking the climate hiatus CLIMATIC CHANGE Rajaratnam, B., Romano, J., Tsiang, M., Diffenbaugh, N. S. 2015; 133 (2): 129-140
  • On stepwise control of directional errors under independence and some dependence JOURNAL OF STATISTICAL PLANNING AND INFERENCE Guo, W., Romano, J. P. 2015; 163: 21-33
  • A PRACTICAL TWO-STEP METHOD FOR TESTING MOMENT INEQUALITIES ECONOMETRICA Romano, J. P., Shaikh, A. M., Wolf, M. 2014; 82 (5): 1979-2002

    View details for DOI 10.3982/ECTA11011

    View details for Web of Science ID 000342905900012

  • Testing for monotonicity in expected asset returns JOURNAL OF EMPIRICAL FINANCE Romano, J. P., Wolf, M. 2013; 23: 93-116
  • EXACT AND ASYMPTOTICALLY ROBUST PERMUTATION TESTS ANNALS OF STATISTICS Chung, E., Romano, J. P. 2013; 41 (2): 484-507

    View details for DOI 10.1214/13-AOS1090

    View details for Web of Science ID 000320488200004

  • Supplement to "Exact and asymptotically robust permutation tests" Annals of Statistics Chung, E., Romano, J. D. 2013; 41

    View details for DOI 10.1214/13-AOS1090SUPP

  • ON THE UNIFORM ASYMPTOTIC VALIDITY OF SUBSAMPLING AND THE BOOTSTRAP ANNALS OF STATISTICS Romano, J. P., Shaikh, A. M. 2012; 40 (6): 2798-2822

    View details for DOI 10.1214/12-AOS1051

    View details for Web of Science ID 000321845400002

  • Subsampling Inference with K Populations and a Non-standard Behrens-Fisher Problem INTERNATIONAL STATISTICAL REVIEW McMurry, T. L., Politis, D. N., Romano, J. P. 2012; 80 (1): 149-175
  • On the third edition of Testing Statistical Hypotheses Selected Works of E.L. Lehmann Romano, J. D. edited by Rojo, J. New York: Springer-Verlag. 2012: 1089–1092
  • Supplement to "On the uniform asymptotic validity of subsampling and the bootstrap" Annals of Statistics Romano, J. D., Shaikh, A. 2012; 40

    View details for DOI 10.1214/12-AOS1041SUPP

  • Consonance and the Closure Method in Multiple Testing INTERNATIONAL JOURNAL OF BIOSTATISTICS Romano, J. P., Shaikh, A., Wolf, M. 2011; 7 (1)
  • K-sample subsampling in general spaces: The case of independent time series JOURNAL OF MULTIVARIATE ANALYSIS Politis, D. N., Romano, J. P. 2010; 101 (2): 316-326
  • BALANCED CONTROL OF GENERALIZED ERROR RATES ANNALS OF STATISTICS Romano, J. P., Wolf, M. 2010; 38 (1): 598-633

    View details for DOI 10.1214/09-AOS734

    View details for Web of Science ID 000273800100018

  • Inference for the Identified Set in Partially Identified Econometric Models ECONOMETRICA Romano, J. P., Shaikh, A. M. 2010; 78 (1): 169-211

    View details for DOI 10.3982/ECTA6706

    View details for Web of Science ID 000274388800006

  • Multiple Testing Romano, J. P., Azeem, S., Michael, W. New Palgrave Dictionary of Economics (Online Edition). 2010
  • Hypothesis Testing in Econometrics ANNUAL REVIEW OF ECONOMICS, VOL 2 Romano, J. P., Shaikh, A. M., Wolf, M. 2010; 2: 75-104
  • Optimal testing of multiple hypotheses with common effect direction BIOMETRIKA Bittman, R. M., Romano, J. P., Vallarino, C., Wolf, M. 2009; 96 (2): 399-410
  • Discussion of 'Parametric versus nonparametrics: two alternative methodologies' JOURNAL OF NONPARAMETRIC STATISTICS Romano, J. P. 2009; 21 (4): 419-424
  • Control of the false discovery rate under dependence using the bootstrap and subsampling TEST Romano, J. P., Shaikh, A. M., Wolf, M. 2008; 17 (3): 417-442
  • Inference for identifiable parameters in partially identified econometric models JOURNAL OF STATISTICAL PLANNING AND INFERENCE Romano, J. P., Shaikh, A. M. 2008; 138 (9): 2786-2807
  • Formalized data snooping based on generalized error rates ECONOMETRIC THEORY Romano, J. P., Shaikh, A. M., Wolf, M. 2008; 24 (2): 404-447
  • K-sample subsampling 1st International Workshop on Functional and Operatorial Statistics Politis, D., Romano, J. PHYSICA-VERLAG GMBH & CO. 2008: 247–253
  • Discussion: On methods controlling the false discover rate Sankya Romano, J. D., Shaikh, A., Wolf, M. 2008; 70: 169-176
  • Control of generalized error rates in multiple testing ANNALS OF STATISTICS Romano, J. P., Wolf, M. 2007; 35 (4): 1378-1408
  • A generalized Sidak-Holm procedure and control of generalized error rates under independence STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY Guo, W., Romano, J. 2007; 6

    Abstract

    For testing multiple null hypotheses, the classical approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, one might be willing to tolerate more than one false rejection provided the number of such cases is controlled, thereby increasing the ability of the procedure to detect false null hypotheses. This suggests replacing control of the FWER by controlling the probability of k or more false rejections, which is called the k-FWER. In Hommel and Hoffmann (1987) and Lehmann and Romano (2005a), single step and stepdown procedures are derived that control the k-FWER, without making any assumptions concerning the dependence structure of the p-values of the individual tests. However, if the p-values are mutually independent, one can improve the procedures. In fact, Sarkar (2005) provided such an improvement. However, we show other improvements are possible which appear to be generally much better, and are sometimes unimprovable. When k=1, the procedure reduces to the classical method of Sidak, and the stepdown procedure is unimprovable and strictly dominates that of Sarkar. Under a monotonicity condition, an unimprovable procedure is obtained. In the case k=2, the monotonicity condition is satisfied, and the condition can be checked numerically in general. We then develop a stepdown method that controls the false discovery proportion. Except for the case of k-FWER control with k=1, the gains are surprisingly dramatic, and theoretical and numerical evidence is given.

    View details for Web of Science ID 000245335600004

    View details for PubMedID 17402918

  • Stepup procedures for control of generalizations of the familywise error rate ANNALS OF STATISTICS Romano, J. P., Shaikh, A. M. 2006; 34 (4): 1850-1873
  • Improved nonparametric confidence intervals in time series regressions JOURNAL OF NONPARAMETRIC STATISTICS Romano, J. P., Wolf, M. 2006; 18 (2): 199-214
  • On stepdown control of the false discovery proportion 2nd Lehmann Symposium-Optimality Romano, J. D., Shaikh, A. edited by Rojo, J. IMS. 2006: 33–50
  • A generalized Sidák procedure and control of generalized error rates under independence Statistical Applications in Genetics and Molecular Biology Guo, W., Romano, J. D. 2006; 6 (1)
  • Stepwise multiple testing as formalized data snooping ECONOMETRICA Romano, J. P., Wolf, M. 2005; 73 (4): 1237-1282
  • Optimal testing of equivalence hypotheses ANNALS OF STATISTICS Romano, J. P. 2005; 33 (3): 1036-1047
  • On optimality of stepdown and stepup multiple test procedures ANNALS OF STATISTICS Lehmann, E. L., Romano, J. P., Shaffer, J. P. 2005; 33 (3): 1084-1108
  • Generalizations of the familywise error rate ANNALS OF STATISTICS Lehmann, E. L., Romano, J. P. 2005; 33 (3): 1138-1154
  • Exact and approximate stepdown methods for multiple hypothesis testing JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Romano, J. R., Wolf, M. 2005; 100 (469): 94-108
  • Testing Statistical Hypotheses Lehmann, E. L., Romano, J. D. New York: Springer-Verlag. 2005
  • On non-parametric testing, the uniform behaviour of the t-test, and related problems SCANDINAVIAN JOURNAL OF STATISTICS Romano, J. P. 2004; 31 (4): 567-584
  • Inference for autocorrelations in the possible presence of a unit root JOURNAL OF TIME SERIES ANALYSIS Politis, D. N., Romano, J. P., Wolf, M. 2004; 25 (2): 251-263
  • Explicit nonparametric confidence intervals for the variance with guaranteed coverage COMMUNICATIONS IN STATISTICS-THEORY AND METHODS Romano, J. P., Wolf, M. 2002; 31 (8): 1231-1250
  • Automatic adaptive estimation via the boostrap Technical Report 2000-01, Department of Statistics, Stanford University Hochster, M., Romano, J. D. 2002
  • On the asymptotic theory of subsampling STATISTICA SINICA Politis, D. N., Romano, J. P., Wolf, M. 2001; 11 (4): 1105-1124
  • Subsampling intervals in autoregressive models with linear time trend ECONOMETRICA Romano, J. P., Wolf, M. 2001; 69 (5): 1283-1314
  • Finite sample nonparametric inference and large sample efficiency ANNALS OF STATISTICS Romano, J. P., Wolf, M. 2000; 28 (3): 756-778
  • A more general central limit theorem for m-dependent random variables with unbounded m STATISTICS & PROBABILITY LETTERS Romano, J. P., Wolf, M. 2000; 47 (2): 115-124
  • Subsampling, symmetrization, and robust interpolation COMMUNICATIONS IN STATISTICS-THEORY AND METHODS Politis, D. N., Romano, J. P., Wolf, M. 2000; 29 (8): 1741-1757
  • Weak convergence of dependent empirical measures with application to subsampling in function spaces JOURNAL OF STATISTICAL PLANNING AND INFERENCE Politis, D., Romano, J. P., Wolf, M. 1999; 79 (2): 179-190
  • On subsampling estimators with unknown rate of convergence JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Bertail, P., Politis, D. N., Romano, J. P. 1999; 94 (446): 569-579
  • An invariance principle for triangular arrays of dependent variables with application to autocovariance estimation CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE Chen, H., Romano, J. P. 1999; 27 (2): 329-343
  • Multivariate density estimation with general flat-top kernels of infinite order JOURNAL OF MULTIVARIATE ANALYSIS Politis, D. N., Romano, J. P. 1999; 68 (1): 1-25
  • Resampling marked point processes Multivariate Analysis, Design of Experiments, and Survey Sampling Paparoditis, E., Politis, D., Romano, J. D. edited by Ghosh, S. New York: Marcel Dekker. 1999: 163–185
  • Bootstrap goodness of fit tests in the frequency domain The Journal of Time Series Chen, H., Romano, J. D. 1999; 20: 619-654
  • Subsampling Politis, D., Romano, J. D., Wolf, M. New York: Springer-Verlag. 1999
  • Subsampling inference for the mean in the heavy-tailed case METRIKA Romano, J. P., Wolf, M. 1999; 50 (1): 55-69
  • Large sample inference for irregularly spaced dependent observations based on subsamples Sankhya Series A Paparoditis, E., Politis, D., Romano, J. D. 1998; 60: 274-292
  • Subsampling confidence intervals for the autoregressive root Technical Report 5, Department of Statistics, Stanford University Romano, J. D., Wolf, M. 1998
  • Subsampling for heteroskedastic time series JOURNAL OF ECONOMETRICS Politis, D. N., Romano, J. P., Wolf, M. 1997; 81 (2): 281-317
  • Inference for autocorrelations under weak assumptions JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Romano, J. P., Thombs, L. A. 1996; 91 (434): 590-600
  • On flat-top kernel spectral density estimators for homogeneous random fields JOURNAL OF STATISTICAL PLANNING AND INFERENCE Politis, D. N., Romano, J. P. 1996; 51 (1): 41-53
  • Subsampling for econometric models Econometric Reviews Politis, D., Romano, J. D. 1996; 15 (2): 169-176
  • ON BOOTSTRAP PROCEDURES FOR 2ND-ORDER ACCURATE CONFIDENCE-LIMITS IN PARAMETRIC MODELS STATISTICA SINICA DiCiccio, T. J., Romano, J. P. 1995; 5 (1): 141-160
  • Bias-corrected nonparametric spectral estimation Journal of Time Series Analysis Politis, D., Romano, J. D. 1995; 16: 67-103
  • THE STATIONARY BOOTSTRAP JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Politis, D. N., Romano, J. P. 1994; 89 (428): 1303-1313
  • LARGE-SAMPLE CONFIDENCE-REGIONS BASED ON SUBSAMPLES UNDER MINIMAL ASSUMPTIONS ANNALS OF STATISTICS Politis, D. N., Romano, J. P. 1994; 22 (4): 2031-2050
  • LIMIT-THEOREMS FOR WEAKLY DEPENDENT HILBERT-SPACE VALUED RANDOM-VARIABLES WITH APPLICATION TO THE STATIONARY BOOTSTRAP STATISTICA SINICA Politis, D. N., Romano, J. P. 1994; 4 (2): 461-476
  • Inference for autocorrelations by resampling Annual Meeting of the American-Statistical-Association, Statistical-Computing-Section Romano, J. P., Thombs, L. A. AMER STATISTICAL ASSOC. 1994: 1–10
  • NONPARAMETRIC RESAMPLING FOR HOMOGENEOUS STRONG MIXING RANDOM-FIELDS JOURNAL OF MULTIVARIATE ANALYSIS Politis, D. N., Romano, J. P. 1993; 47 (2): 301-328
  • ON THE SAMPLE VARIANCE OF LINEAR STATISTICS DERIVED FROM MIXING SEQUENCES STOCHASTIC PROCESSES AND THEIR APPLICATIONS Politis, D. N., Romano, J. P. 1993; 45 (1): 155-167
  • ON A FAMILY OF SMOOTHING KERNELS OF INFINITE-ORDER 25th Symposium on the Interface of Computing Science and Statistics - Statistical Applications of Expanding Computer Capabilities Politis, D. N., Romano, J. P. INTERFACE FOUNDATION NORTH AMERICA. 1993: 141–145
  • Estimating the distribution of a studentized statistic by subsampling Bulletin of the International Statistical Institute Politis, D., Romano, J. 1993; 49: 315-316
  • UNIFORM CONFIDENCE BANDS FOR THE SPECTRUM BASED ON SUBSAMPLES 25th Symposium on the Interface of Computing Science and Statistics - Statistical Applications of Expanding Computer Capabilities Politis, D. N., Romano, J. P., You, L. F. INTERFACE FOUNDATION NORTH AMERICA. 1993: 346–351
  • A GENERAL RESAMPLING SCHEME FOR TRIANGULAR ARRAYS OF ALPHA-MIXING RANDOM-VARIABLES WITH APPLICATION TO THE PROBLEM OF SPECTRAL DENSITY-ESTIMATION ANNALS OF STATISTICS Politis, D. N., Romano, J. P. 1992; 20 (4): 1985-2007
  • BOOTSTRAP TECHNOLOGY AND APPLICATIONS TECHNOMETRICS Leger, C., Politis, D. N., Romano, J. P. 1992; 34 (4): 378-398
  • BOOTSTRAP CONFIDENCE BANDS FOR SPECTRA AND CROSS-SPECTRA IEEE TRANSACTIONS ON SIGNAL PROCESSING Politis, D. N., Romano, J. P., Lai, T. L. 1992; 40 (5): 1206-1215
  • A nonparametric resampling procedure for multivariate confidence regions in time series analysis Proceedings of the 22nd Symposium on the Interface Politis, D., Romano, J. D. edited by Page, C., LePage, R. 1992: 98–103
  • A circular block-resampling procedure for stationary data Exploring the Limits of Bootstrap Politis, D., Romano, J. D. edited by LePage, R., Billard, L. John Wiley. 1992: 263–270
  • EMPIRICAL LIKELIHOOD IS BARTLETT-CORRECTABLE ANNALS OF STATISTICS DICICCIO, T., Hall, P., Romano, J. 1991; 19 (2): 1053-1061
  • BOOTSTRAP ADAPTIVE ESTIMATION - THE TRIMMED-MEAN EXAMPLE CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE Leger, C., Romano, J. P. 1990; 18 (4): 297-314
  • BOOTSTRAP CHOICE OF TUNING PARAMETERS ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Leger, C., Romano, J. P. 1990; 42 (4): 709-735
  • ON THE BEHAVIOR OF RANDOMIZATION TESTS WITHOUT A GROUP INVARIANCE ASSUMPTION JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Romano, J. P. 1990; 85 (411): 686-692
  • NONPARAMETRIC CONFIDENCE-LIMITS BY RESAMPLING METHODS AND LEAST FAVORABLE FAMILIES INTERNATIONAL STATISTICAL REVIEW DiCiccio, T. J., Romano, J. P. 1990; 58 (1): 59-76
  • ON ADJUSTMENTS BASED ON THE SIGNED ROOT OF THE EMPIRICAL LIKELIHOOD RATIO STATISTIC BIOMETRIKA DiCiccio, T. J., Romano, J. P. 1989; 76 (3): 447-456
  • COMPARISON OF PARAMETRIC AND EMPIRICAL LIKELIHOOD FUNCTIONS BIOMETRIKA DiCiccio, T. J., Hall, P., Romano, J. P. 1989; 76 (3): 465-476
  • ON SMOOTHING AND THE BOOTSTRAP ANNALS OF STATISTICS Hall, P., DiCiccio, T. J., Romano, J. P. 1989; 17 (2): 692-704
  • THE AUTOMATIC PERCENTILE METHOD - ACCURATE CONFIDENCE-LIMITS IN PARAMETRIC MODELS CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE DiCiccio, T. J., Romano, J. P. 1989; 17 (2): 155-169
  • BOOTSTRAP AND RANDOMIZATION TESTS OF SOME NONPARAMETRIC HYPOTHESES ANNALS OF STATISTICS Romano, J. P. 1989; 17 (1): 141-159
  • DO BOOTSTRAP CONFIDENCE PROCEDURES BEHAVE WELL UNIFORMLY IN P CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE Romano, J. P. 1989; 17 (1): 75-80
  • A BOOTSTRAP REVIVAL OF SOME NONPARAMETRIC DISTANCE TESTS JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Romano, J. P. 1988; 83 (403): 698-708
  • THEORETICAL COMPARISON OF BOOTSTRAP CONFIDENCE-INTERVALS - DISCUSSION ANNALS OF STATISTICS DiCiccio, T. J., Romano, J. P. 1988; 16 (3): 965-969
  • ON WEAK-CONVERGENCE AND OPTIMALITY OF KERNEL DENSITY ESTIMATES OF THE MODE ANNALS OF STATISTICS Romano, J. P. 1988; 16 (2): 629-647
  • BOOTSTRAP METHODS - A REVIEW OF BOOTSTRAP CONFIDENCE-INTERVALS - DISCUSSION JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL Kent, J. T., Davison, A. C., Silverman, B. W., Young, G. A., Daniels, H. E., Tong, H., Garthwaite, P. H., Buckland, S. T., Beran, R., Hall, P., KOSLOW, S., Stewart, D. W., Tibshirani, R. J., Titterington, D. M., Verrall, R. J., Wynn, H. P., Wu, C. F., Hinkley, D., DiCiccio, T. J., Romano, J. P. 1988; 50 (3): 355-370
  • A REVIEW OF BOOTSTRAP CONFIDENCE-INTERVALS JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL DiCiccio, T. J., Romano, J. P. 1988; 50 (3): 338-354
  • BOOTSTRAPPING THE MODE ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Romano, J. P. 1988; 40 (3): 565-586
  • Counterexamples in Probability and Statistics Romano, J. P., Siegel, A. F. Monterey, CA: Wadsworth Publishing Company. 1986
  • BOOTSTRAP CONFIDENCE CONES FOR DIRECTIONAL-DATA BIOMETRIKA Ducharme, G. R., Jhun, M., Romano, J. P., TRUONG, K. N. 1985; 72 (3): 637-645
  • Evaluating inclusion functionals for random convex hulls Z. Wahrscheinlichkeitsth Jewell, N. P., Romano, J. P. 1985; 68: 415-424
  • COVERAGE PROBLEMS AND RANDOM CONVEX HULLS JOURNAL OF APPLIED PROBABILITY Jewell, N. P., Romano, J. P. 1982; 19 (3): 546-561