DOCSLIB.ORG

How Do Statisticians Perceive Statistics Journals?

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
How Do Statisticians Perceive Statistics Journals? General How DoStatisticians Perceive Statistics Journals? Vasilis THEOHARAKIS and Mary SKORDIA ceptionsof statisticians with different research interests may vary.In fact, in the UK wherefunds to universitiesare disbursed Sinceresearchers and academic institutions are increasingly basedon theResearch Assessment Exercise (RAE), impactfac- evaluatedbased on their publication record in peer reviewed torsor citationindices are not used to assessresearch output in journals,it is crucial to assess how the statistics community journals.Instead, the assessment of the RAE panelfor statis- perceivesstatistics journals. This study presents four subjective ticsis basedon the “ perceivededitorial standards of journals” qualitymetrics of statistics journals as expressed by different (http://www.hero.ac.uk/rae/criteria/crit24.htm). segmentsof statisticians. Based on aworldwidesample of 2,190 Despitethe fact that the assessment of journalsis acrucialis- statisticians,our ndingsindicate that the research interest and suefor theresearch community, it is asurprisethat the statistics geographicorigin of theresearcher have a signicant impact on community’s perceptionshave not been systematically exam- journalperceptions, which are highly correlated with a journal’s ined.W ethereforepose the following questions: What are the totalnumber of citations. mostpopular journals in the eldof statistics?Since promotion decisionsfrequently depend on the number of publications in KEY WORDS: Journalrankings; Statistics research. toptier journals, how do statisticians classify journals in tiers? Besidesone’ s perceptionabout a journal’s standing,how useful doresearchers nda particularjournal? Do statisticians from differentresearch or geographicareas or witha differenttype 1.INTRODUCTION ofemploymentvalue journals differently? How dothesubjec- Therecognition and development of anacademicinstitution tiveperceptions of journal quality relate to the more objective dependsheavily on its faculty’ s publicationrecord in presti- journalcitation measures? By addressing these questions, this giousjournals (Lane, Ray, and Glennon 1990). As aresult,an studyseeks to assist: (1) authorsin their search for aresearch increasedemphasis is placed on publishing in refereed jour- outlet,(2) departmentsin promotionand tenure decisions, and nalsand promotion criteria rest heavily on the faculty’ s pub- (3) journaleditors, by providingthem a viewof their journal’ s licationrecord (Gibbons 1990). In fact, not only is the pub- standing.W eshouldnote that while we examinethe percep- licationrecord one of the criteria for selectingFellows at the tualjournal rankings, there is a substantialoverlap in the quality AmericanStatistical Association (Bailar 1988), but it is also ofindividualarticles that appear in journalsof vastlydifferent usedto measure the productivity of countries and institutions reputation. for theircontributions to statistics (Genest 1997). Genest mea- suredinstitution and country research productivity based on the 2.SUR VEY INSTRUMENT AND METHODOLOGY numberof articles,number of authors, and page counts in 16 Sincewe soughtto examine journal perceptions over a broad internationaljournals publishing in statistical theory. Since he sample,we locatedfour publicly available membership direc- believedthe selection of these journals to be “ subjectiveand toriesof statisticians (American Statistical Association, Insti- far from comprehensive,”astudythat systematically identi es tuteof Mathematical Statistics, International Statistical Institute, therelevant journals would facilitate such studies. The need for andan online listing of UK-basedacademic statisticians, found identifyingrelevant journals was alsodemonstrated by Baltagi athttp:/ /www.swan.ac.uk/statistics/das/).Dueto thepervasive (1999)in his article on the ranking of individuals and institu- useof theInternet among statisticians, we developedan online tionsin applied econometrics. T odemonstrateimpact, Baltagi survey.Our questionnairerequested from participantsto place usedpage counts and citations of relevant articles from 15jour- statisticsjournals in rank order and at the same time provide nals,but could not control for journalquality since no jour- demographicinformation. The demographic variables were se- nalquality measure was available.Although citation reports do lectedin orderto beused as segmentation variables that could providean aggregate measure of a journal’s impact,the per- provideanswers tothequestions raised earlier .Therefore,par- ticipantswere askedto rank up totenstatistics journals that they Vasilis Theoharakisis Assistant Professor(E-mail: [email protected]), consideredas top tier (most rigorous, prestigious, and impor- andMary Skordia is Research Associate, AthensLaboratory of Business Admin- tant)and up to ten additional journals that they considered as istration(ALBA), Athinas & Areos 2A,V ouliagmeni166 71, Athens, Greece. secondtier. In addition, respondents were askedto list up toten Thisarticle wouldnot have been in place withoutthe support of colleagues who journalsthat they considered to bemostuseful in their work. A spentmany hours in providing direct input and feedback. The authors thank the editorand associate editorfor their very constructive comments thatsigni cantly listof 110 statistics journals was availableon pull-downmenus improvedthis article. (Appendix),but respondents could also llin anyother journal c 2003American Statistical Association DOI: 10.1198/0003130031414 TheAmerican Statistician, May 2003, V ol.57, No. 2 115 ® Table1. Respondents’ Pro le follows: 20 Highestacademic degree Rij j ARP = j= 1 ¤ (1 ARP 20); (1) Doctorate 1734 i 20 µ i µ Masters 355 P j= 1 Rij Bachelor’s 40 Other 24 where i denotesthe journal P and Rij isthe number of timesjour- No answer 37 nal i hasbeen ranked in the jthposition. Thus, a lowerARP TOTAL 2190 denotesa higherperceived journal importance. In addition, we reportthe percentage of respondentswho included the journal Typeof employment Facultymember 1234 intheir top ten with respect to thetotal number of respondents Governmentemployee 185 (%Top10)andjournal Usefulness thatcorresponds to the per- Researcher/clinicianat ahealth/medicalfacility 152 centageof respondents who listed the journal among the ones Manufacturingindustry employee 121 mostuseful in their work. But one hasto becarefulwhen ranking Privateconsultant 101 Serviceindustry employee 43 journalson anysingle measure of perceived quality. For exam- Retired 32 ple,if journal A isranked by 100 respondents who all place it in Actuary 3 the1st rst positionand journal B isranked by 101 respondents Other 179 whoall place it in the 20th position, then journal A wouldbe No answer 140 TOTAL 2190 rankedlower if journals were rankedbased on Familiarity. In orderto minimizesuch problems, we consideredmultiple qual- Geographicallocation itymeasures when performing the ranking of journals,by using NorthAmerica 1495 Index Europe 412 a weighted offamiliarityand rank (Theoharakis and Hirst Asia 149 2002)that is de ned as follows: LatinAmerica 57 20 Australia/New Zealand 37 Rij (21 j) Index = 100 j= 1 ¤ ¡ Africa 23 i ¤ 20 n No answer 17 P 21 ARP¤ TOTAL 2190 = 100 ¡ i %Top20 ¤ 20 ¤ i (0 Indexi 100); (2) titlethey wished. From thedirectories identi ed, we collected µ µ theE-mail addresses of 12,053 statisticians and proceeded by where i denotesthe journal and Rij isthe number of times sendingan E-mail invitation to themfor completingour online the journal i hasbeen ranked in the jthposition and n is the questionnaire(the questionnaire and full set of tablesare avail- numberof respondentsin the sample. Thus, the Index assigns to the jthposition a decreasingweight of (21 j)=20, with the ableat www.alba.edu.gr/ survey).The survey was pretestedon ¡ asampleof 30 statisticiansand minor alternations were made. rst rankposition carrying a weightof 20/20andthe last (20th) Twoweeks after the initialE-mail invitation, an E-mail reminder positiona weightof 1/ 20.W ealsoextend the original Index was sentto individuals who had not responded. byTheoharakisand Hirst (2002)to indicateits connectionwith Intotal, we received2,190 usable responses (521 from thesec- ARP and%T op20.As we listthe journalsbased on this Index, we ondwave) with a usableresponse rate of 18.2%.No signi cant presenteach individual measure and suggest that readers should differencesin the ranking of journalswere foundbetween rst examineeach journal individually across the metrics presented. andsecond wave respondents, that is, those who responded to thereminder E-mail, which may indicate that our sample does 3. RESULTS notsuffer from nonresponsebias. However, statisticians that donot believe in ranking journals, may have not participated. Wepresentjournals based on the weighted Index of famil- Nearlytwo-thirds of ourrespondents are from NorthAmerica, iarityand rank for ourworldwide sample and the two largest morethan half are faculty members, and nearly 80% of ourre- regionalsamples (T able2). Although the correlations between spondentshold a doctorate(T able1). Sixty seven percent of our ourperceptual metrics (%T op10,%T op20,ARP, andUseful- respondentsreplied that their institution uses the number and/ or ness)are high (T able3), the correlations of eachone of these characterof journalpublications for personneldecisions. metricswith our Index are even higher; the only exception is thecorrelation of ARP with%T op10that is about the same with thecorrelation of ARP withIndex (this is nota surprisesince %Top10depends on rankposition).
Load more

Recommended publications
  • BIOGRAPHICAL SKETCH Garrett M. Fitzmaurice Associate Professor Of
    Principal Investigator/Program Director (Last, First, Middle): BIOGRAPHICAL SKETCH Provide the following information for the key personnel and other significant contributors in the order listed on Form Page 2. Follow this format for each person. DO NOT EXCEED FOUR PAGES. NAME POSITION TITLE Garrett M. Fitzmaurice Associate Professor of Biostatistics eRA COMMONS USER NAME EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, and include postdoctoral training.) DEGREE INSTITUTION AND LOCATION YEAR(s) FIELD OF STUDY (if applicable) National University of Ireland BA, MA 1983, 1987 Psychology University of London MSc 1986 Quantitative Methods Harvard University ScD 1993 Biostatistics Professional Experience: 1986-1989 Statistician, Department of Psychology, New York University 1989-1990 Teaching Assistant, Department of Biostatistics, Harvard School of Public Health 1990-1993 Teaching Fellow in Biostatistics, Department of Biostatistics, Harvard SPH 1993-1994 Post-doctoral Research Fellow, Department of Biostatistics, Harvard SPH 1994-1997 Research Fellow, Nuffield College, Oxford University, United Kingdom 1997-1999 Assistant Professor of Biostatistics, Harvard School of Public Health 1999-present Associate Professor of Biostatistics, Harvard School of Public Health 2004-present Associate Professor of Medicine (Biostatistics), Harvard Medical School 2004-present Biostatistician, Division of General Medicine, Brigham and Women’s Hospital, Boston 2006-present Foreign Adjunct Professor of Biostatistics,
    [Show full text]
  • Publishing and Promotion in Economics: the Curse of the Top Five
    Publishing and Promotion in Economics: The Curse of the Top Five James J. Heckman 2017 AEA Annual Meeting Chicago, IL January 7th, 2017 Heckman Curse of the Top Five Top 5 Influential, But Far From Sole Source of Influence or Outlet for Creativity Heckman Curse of the Top Five Table 1: Ranking of 2, 5 and 10 Year Impact Factors as of 2015 Rank 2 Years 5 Years 10 Years 1. JEL JEL JEL 2. QJE QJE QJE 3. JOF JOF JOF 4. JEP JEP JPE 5. ReStud JPE JEP 6. ECMA AEJae ECMA 7. AEJae ECMA AER 8. AER AER ReStud 9. JPE ReStud JOLE 10. JOLE AEJma EJ 11. AEJep AEJep JHR 12. AEJma EJ JOE 13. JME JOLE JME 14. EJ JHR HE 15. HE JME RED 16. JHR HE EER 17. JOE JOE - 18. AEJmi AEJmi - 19. RED RED - 20. EER EER - Note: Definition of abbreviated names: JEL - Journal of Economic Literature, JOF - Journal of Finance, JEP - Journal of Economic Perspectives, AEJae-American Economic Journal Applied Economics, AER - American Economic Review, JOLE-Journal of Labor Economics, AEJep-American Economic Journal Economic Policy, AEJma-American Economic Journal Macroeconomics, JME-Journal of Monetary Economics, EJ-Economic Journal, HE-Health Economics, JHR-Journal of Human Resources, JOE-Journal of Econometrics, AEJmi-American Economic Journal Microeconomics, RED-Review of Economic Dynamics, EER-European Economic Review; Source: Journal Citation Reports (Thomson Reuters, 2016). Heckman Curse of the Top Five Figure 1: Articles Published in Last 10 years by RePEc's T10 Authors (Last 10 Years Ranking) (a) T10 Authors (Unadjusted) (b) T10 Authors (Adjusted) Prop.
    [Show full text]
  • Brendan K. Beare
    Brendan K. Beare Department of Economics University of California – San Diego 9500 Gilman Drive #0508 La Jolla, California 92093, U.S.A. Email: [email protected] : http://econweb.ucsd.edu/ bbeare/ ∼ Born: January 23, 1980 Citizenship: Australia & United States Current position 2015– Associate Professor, University of California – San Diego Prior appointments held 2008–2015 Assistant Professor, University of California – San Diego 2007–2008 Research Fellow, Nuffield College and University of Oxford Education 2007 PD in Economics, Yale University 2006 MA in Statistics, Yale University 2005 MP in Economics, Yale University 2004 MA in Economics, Yale University 2002 BE(H) in Econometrics, University of New South Wales Honors & awards 2011–2016 Sir Clive W. J. Granger Chair, University of California – San Diego 2008 George Trimis Prize for Distinguished Dissertation in Economics, Yale University 2007 MA by Resolution, University of Oxford 2007 Dissertation Fellowship, Yale University 2006 Carl Arvid Anderson Prize, Cowles Foundation for Research in Economics 2006 Cowles Summer Prize, Cowles Foundation for Research in Economics 2002–2006 Cowles Prize, Cowles Foundation for Research in Economics 2002–2006 University Fellowship, Yale University 2002 Economic Society of Australia Honours Prize 1 Publications 2019 Beare, Brendan K. and Shi, Xiaoxia. An improved bootstrap test of density ratio ordering. Econometrics and Statistics, 10: 9-26. 2019 Seo, Won-Ki and Beare, Brendan K. Cointegrated linear processes in Bayes Hilbert space. Statistics and Probability Letters, 147: 90-95. 2018 Beare, Brendan K. Unit root testing with unstable volatility. Journal of Time Series Analysis, 39(6): 816-835. 2018 Beare, Brendan K. and Dossani, Asad. Option augmented density forecasts of market returns with monotone pricing kernel.
    [Show full text]
  • Report on Statistical Disclosure Limitation Methodology
    STATISTICAL POLICY WORKING PAPER 22 (Second version, 2005) Report on Statistical Disclosure Limitation Methodology Federal Committee on Statistical Methodology Originally Prepared by Subcommittee on Disclosure Limitation Methodology 1994 Revised by Confidentiality and Data Access Committee 2005 Statistical and Science Policy Office of Information and Regulatory Affairs Office of Management and Budget December 2005 The Federal Committee on Statistical Methodology (December 2005) Members Brian A. Harris-Kojetin, Chair, Office of William Iwig, National Agricultural Management and Budget Statistics Service Wendy L. Alvey, Secretary, U.S. Census Arthur Kennickell, Federal Reserve Board Bureau Nancy J. Kirkendall, Energy Information Lynda Carlson, National Science Administration Foundation Susan Schechter, Office of Management and Steven B. Cohen, Agency for Healthcare Budget Research and Quality Rolf R. Schmitt, Federal Highway Steve H. Cohen, Bureau of Labor Statistics Administration Lawrence H. Cox, National Center for Marilyn Seastrom, National Center for Health Statistics Education Statistics Robert E. Fay, U.S. Census Bureau Monroe G. Sirken, National Center for Health Statistics Ronald Fecso, National Science Foundation Nancy L. Spruill, Department of Defense Dennis Fixler, Bureau of Economic Analysis Clyde Tucker, Bureau of Labor Statistics Gerald Gates, U.S. Census Bureau Alan R. Tupek, U.S. Census Bureau Barry Graubard, National Cancer Institute G. David Williamson, Centers for Disease Control and Prevention Expert Consultant Robert Groves, University of Michigan and Joint Program in Survey Methodology Preface The Federal Committee on Statistical Methodology (FCSM) was organized by the Office of Management and Budget (OMB) in 1975 to investigate issues of data quality affecting Federal statistics. Members of the committee, selected by OMB on the basis of their individual expertise and interest in statistical methods, serve in a personal capacity rather than as agency representatives.
    [Show full text]
  • TUTORIAL in BIOSTATISTICS: the Self-Controlled Case Series Method
    STATISTICS IN MEDICINE Statist. Med. 2005; 0:1–31 Prepared using simauth.cls [Version: 2002/09/18 v1.11] TUTORIAL IN BIOSTATISTICS: The self-controlled case series method Heather J. Whitaker1, C. Paddy Farrington1, Bart Spiessens2 and Patrick Musonda1 1 Department of Statistics, The Open University, Milton Keynes, MK7 6AA, UK. 2 GlaxoSmithKline Biologicals, Rue de l’Institut 89, B-1330 Rixensart, Belgium. SUMMARY The self-controlled case series method was developed to investigate associations between acute outcomes and transient exposures, using only data on cases, that is, on individuals who have experienced the outcome of interest. Inference is within individuals, and hence fixed covariates effects are implicitly controlled for within a proportional incidence framework. We describe the origins, assumptions, limitations, and uses of the method. The rationale for the model and the derivation of the likelihood are explained in detail using a worked example on vaccine safety. Code for fitting the model in the statistical package STATA is described. Two further vaccine safety data sets are used to illustrate a range of modelling issues and extensions of the basic model. Some brief pointers on the design of case series studies are provided. The data sets, STATA code, and further implementation details in SAS, GENSTAT and GLIM are available from an associated website. key words: case series; conditional likelihood; control; epidemiology; modelling; proportional incidence Copyright c 2005 John Wiley & Sons, Ltd. 1. Introduction The self-controlled case series method, or case series method for short, provides an alternative to more established cohort or case-control methods for investigating the association between a time-varying exposure and an outcome event.
    [Show full text]
  • Alberto Abadie
    ALBERTO ABADIE Office Address Massachusetts Institute of Technology Department of Economics 50 Memorial Drive Building E52, Room 546 Cambridge, MA 02142 E-mail: [email protected] Academic Positions Massachusetts Institute of Technology Cambridge, MA Professor of Economics, 2016-present IDSS Associate Director, 2016-present Harvard University Cambridge, MA Professor of Public Policy, 2005-2016 Visiting Professor of Economics, 2013-2014 Associate Professor of Public Policy, 2004-2005 Assistant Professor of Public Policy, 1999-2004 University of Chicago Chicago, IL Visiting Assistant Professor of Economics, 2002-2003 National Bureau of Economic Research (NBER) Cambridge, MA Research Associate (Labor Studies), 2009-present Faculty Research Fellow (Labor Studies), 2002-2009 Non-Academic Positions Amazon.com, Inc. Seattle, WA Academic Research Consultant, 2020-present Education Massachusetts Institute of Technology Cambridge, MA Ph.D. in Economics, 1995-1999 Thesis title: \Semiparametric Instrumental Variable Methods for Causal Response Mod- els." Centro de Estudios Monetarios y Financieros (CEMFI) Madrid, Spain M.A. in Economics, 1993-1995 Masters Thesis title: \Changes in Spanish Labor Income Structure during the 1980's: A Quantile Regression Approach." 1 Universidad del Pa´ıs Vasco Bilbao, Spain B.A. in Economics, 1987-1992 Specialization Areas: Mathematical Economics and Econometrics. Honors and Awards Elected Fellow of the Econometric Society, 2016. NSF grant SES-1756692, \A General Synthetic Control Framework of Estimation and Inference," 2018-2021. NSF grant SES-0961707, \A General Theory of Matching Estimation," with G. Imbens, 2010-2012. NSF grant SES-0617810, \The Economic Impact of Terrorism: Lessons from the Real Estate Office Markets of New York and Chicago," with S. Dermisi, 2006-2008.
    [Show full text]
  • Econometric Theory
    Econometric Theory John Stachurski January 10, 2014 Contents Preface v I Background Material1 1 Probability2 1.1 Probability Models.............................2 1.2 Distributions................................. 16 1.3 Dependence................................. 25 1.4 Asymptotics................................. 30 1.5 Exercises................................... 39 2 Linear Algebra 49 2.1 Vectors and Matrices............................ 49 2.2 Span, Dimension and Independence................... 59 2.3 Matrices and Equations........................... 66 2.4 Random Vectors and Matrices....................... 71 2.5 Convergence of Random Matrices.................... 74 2.6 Exercises................................... 79 i CONTENTS ii 3 Projections 84 3.1 Orthogonality and Projection....................... 84 3.2 Overdetermined Systems of Equations.................. 90 3.3 Conditioning................................. 93 3.4 Exercises................................... 103 II Foundations of Statistics 107 4 Statistical Learning 108 4.1 Inductive Learning............................. 108 4.2 Statistics................................... 112 4.3 Maximum Likelihood............................ 120 4.4 Parametric vs Nonparametric Estimation................ 125 4.5 Empirical Distributions........................... 134 4.6 Empirical Risk Minimization....................... 137 4.7 Exercises................................... 149 5 Methods of Inference 153 5.1 Making Inference about Theory...................... 153 5.2 Confidence Sets..............................
    [Show full text]
  • Miguel De Carvalho
    School of Mathematics Miguel de Carvalho Contact M. de Carvalho T: +44 (0) 0131 650 5054 Information The University of Edinburgh B: [email protected] School of Mathematics : mb.carvalho Edinburgh EH9 3FD, UK +: www.maths.ed.ac.uk/ mdecarv Personal Born September 20, 1980 in Montijo, Lisbon. Details Portuguese and EU citizenship. Interests Applied Statistics, Biostatistics, Econometrics, Risk Analysis, Statistics of Extremes. Education Universidade de Lisboa, Portugal Habilitation in Probability and Statistics, 2019 Thesis: Statistical Modeling of Extremes Universidade Nova de Lisboa, Portugal PhD in Mathematics with emphasis on Statistics, 2009 Thesis: Extremum Estimators and Stochastic Optimization Advisors: Manuel Esqu´ıvel and Tiago Mexia Advisors of Advisors: Jean-Pierre Kahane and Tiago de Oliveira. Nova School of Business and Economics (Triple Accreditation), Portugal MSc in Economics, 2009 Thesis: Mean Regression for Censored Length-Biased Data Advisors: Jos´eA. F. Machado and Pedro Portugal Advisors of Advisors: Roger Koenker and John Addison. Universidade Nova de Lisboa, Portugal `Licenciatura'y in Mathematics, 2004 Professional Probation Period: Statistics Portugal (Instituto Nacional de Estat´ıstica). Awards & ISBA (International Society for Bayesian Analysis) Honours Lindley Award, 2019. TWAS (Academy of Sciences for the Developing World) Young Scientist Prize, 2015. International Statistical Institute Elected Member, 2014. American Statistical Association Young Researcher Award, Section on Risk Analysis, 2011. National Institute of Statistical Sciences j American Statistical Association Honorary Mention as a Finalist NISS/ASA Best y-BIS Paper Award, 2010. Portuguese Statistical Society (Sociedade Portuguesa de Estat´ıstica) Young Researcher Award, 2009. International Association for Statistical Computing ERS IASC Young Researcher Award, 2008. 1 of 13 p l e t t si a o e igulctoson Applied Statistical ModelingPublications 1.
    [Show full text]
  • Biometrics & Biostatistics
    Hanley and Moodie, J Biomet Biostat 2011, 2:5 Biometrics & Biostatistics http://dx.doi.org/10.4172/2155-6180.1000124 Research Article Article OpenOpen Access Access Sample Size, Precision and Power Calculations: A Unified Approach James A Hanley* and Erica EM Moodie Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Canada Abstract The sample size formulae given in elementary biostatistics textbooks deal only with simple situations: estimation of one, or a comparison of at most two, mean(s) or proportion(s). While many specialized textbooks give sample formulae/tables for analyses involving odds and rate ratios, few deal explicitly with statistical considera tions for slopes (regression coefficients), for analyses involving confounding variables or with the fact that most analyses rely on some type of generalized linear model. Thus, the investigator is typically forced to use “black-box” computer programs or tables, or to borrow from tables in the social sciences, where the emphasis is on cor- relation coefficients. The concern in the – usually very separate – modules or stand alone software programs is more with user friendly input and output. The emphasis on numerical exactness is particularly unfortunate, given the rough, prospective, and thus uncertain, nature of the exercise, and that different textbooks and software may give different sample sizes for the same design. In addition, some programs focus on required numbers per group, others on an overall number. We present users with a single universal (though sometimes approximate) formula that explicitly isolates the impacts of the various factors one from another, and gives some insight into the determinants for each factor.
    [Show full text]
  • JEROME P. REITER Department of Statistical Science, Duke University Box 90251, Durham, NC 27708 Phone: 919 668 5227
    JEROME P. REITER Department of Statistical Science, Duke University Box 90251, Durham, NC 27708 phone: 919 668 5227. email: [email protected]. September 26, 2021 EDUCATION Ph.D. in Statistics, Harvard University, 1999. A.M. in Statistics, Harvard University, 1996. B.S. in Mathematics, Duke University, 1992. DISSERTATION \Estimation in the Presence of Constraints that Prohibit Explicit Data Pooling." Advisor: Donald B. Rubin. POSITIONS Academic Appointments Professor of Statistical Science and Bass Fellow, Duke University, 2015 - present. Mrs. Alexander Hehmeyer Professor of Statistical Science, Duke University, 2013 - 2015. Mrs. Alexander Hehmeyer Associate Professor of Statistical Science, Duke University, 2010 - 2013. Associate Professor of Statistical Science, Duke University, 2009 - 2010. Assistant Professor of Statistical Science, Duke University, 2006 - 2008. Assistant Professor of the Practice of Statistics and Decision Sciences, Duke University, 2002 - 2006. Lecturer in Statistics, University of California at Santa Barbara, 2001 - 2002. Assistant Professor of Statistics, Williams College, 1999 - 2001. Other Appointments Chair, Department of Statistical Science, Duke University, 2019 - present. Associate Chair, Department of Statistical Science, Duke University, 2016 - 2019. Mathematical Statistician (part-time), U. S. Bureau of the Census, 2015 - present. Associate/Deputy Director of Information Initiative at Duke, Duke University, 2013 - 2019. Social Sciences Research Institute Data Services Core Director, Duke University, 2010 - 2013. Interim Director, Triangle Research Data Center, 2006. Senior Fellow, National Institute of Statistical Sciences, 2002 - 2005. 1 ACADEMIC HONORS Keynote talk, 11th Official Statistics and Methodology Symposium (Statistics Korea), 2021. Fellow of the Institute of Mathematical Statistics, 2020. Clifford C. Clogg Memorial Lecture, Pennsylvania State University, 2020 (postponed due to covid-19).
    [Show full text]
  • Biostatistics Student Paper Competition the Department of Biostatistics at BUSPH Is Soliciting Applications for the 2013 Student Paper Competition
    Biostatistics Student Paper Competition The Department of Biostatistics at BUSPH is soliciting applications for the 2013 student paper competition. The competition is open to all students enrolled in the Biostatistics Program at Boston University in the spring term of 2013. The winner of the competition will receive $750 as a travel award to attend the summer Joint Statistical Meetings. Travel to other conferences (i.e. ENAR, Society for Clinical Trials, American Society of Human Genetics, International Genetic Epidemiology Society) is possible in negotiation with the award committee. All students are strongly encouraged to submit the abstracts from their papers to the Joint Statistical Meetings, which has a deadline of February 4th. Students would also be encouraged to consider entering the competitions sponsored by sections of the Joint Statistical Meetings (e.g. The Biometrics section Byar Young Investigator award, for details see http://www.bio.ri.ccf.org/Biometrics/winner.html). TIMETABLE: January 11th, 2013 at noon: Deadline for students to submit pdf of manuscript January 25th, 2013: Announcement of awards REQUIREMENTS: The paper should be prepared double spaced, in manuscript format, using guidelines for authors typical of a biostatistical journal (e.g. Biometrics, Statistics in Medicine, or Biostatistics). A pdf copy of the manuscript should be submitted to the chair of the award committee, Ching-Ti Liu ([email protected]). The reported work should be relevant to biostatistics and must be the work of the student, although the manuscript can be co-authored with a faculty advisor or a small number of collaborators. The student must be the first author of the manuscript.
    [Show full text]
  • Biometrical Applications in Biological Sciences-A Review on the Agony for Their Practical Efficiency- Problems and Perspectives
    Biometrics & Biostatistics International Journal Review Article Open Access Biometrical applications in biological sciences-A review on the agony for their practical efficiency- Problems and perspectives Abstract Volume 7 Issue 5 - 2018 The effect of the three biological sciences- agriculture, environment and medicine S Tzortzios in the people’s life is of the greatest importance. The chain of the influence of the University of Thessaly, Greece environment to the form and quality of the agricultural production and the effect of both of them to the people’s health and welfare consists in an integrated system Correspondence: S Tzortzios, University of Thessaly, Greece, that is the basic substance of the human life. Agriculture has a great importance in Email [email protected] the World’s economy; however, the available resources for research and technology development are limited. Moreover, the environmental and productive conditions are Received: August 12, 2018 | Published: October 05, 2018 very different from one country to another, restricting the generalized transferring of technology. The statistical methods should play a paramount role to insure both the objectivity of the results of agricultural research as well as the optimum usage of the limited resources. An inadequate or improper use of statistical methods may result in wrong conclusions and in misuse of the available resources with important scientific and economic consequences. Many times, Statistics is used as a basis to justify conclusions of research work without considering in advance the suitability of the statistical methods to be used. The obvious question is: What importance do biological researchers give to the statistical methods? The answer is out of any doubt and the fact that most of the results published in specialized journals includes statistical considerations, confirms its importance.
    [Show full text]