StatisticsNewS Fit linear models without intercepts in SAS or R Routines for linear models in SAS and R incorporate an intercept by default. But, what's the syntax for fitting a model without an intercept? This entry from SAS and R: Data Management, Statistical Analysis, and Graphics (July 2009) will tell you. The book is designed as a bilingual SAS/R dictionary: If you know SAS, you can look up the noint option in the SAS index. If you know R, you can look up the 0 operator, or if you're unaware of how to do it in either, you can look up no intercept in the subject index.
SAS proc glm data=ds; model y = x1 ... xk / noint; run; Note: The noint option works with many model statements.
R mod1 < –lm(y ~ 0 + x1 + ... + xk, data=ds) or mod1 < –lm(y ~ x1 + ... + xk –1, data=ds)
Nexus
Making the Most Out of those Complex Datasets in the Social and Behavioral Sciences Large and complex datasets are becoming increasingly prevalent in the social and behavioral sciences. The Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series makes the lives of statisticians working in the applied sciences easier by exploring the effective and efficient use of statistical, econometric, and psychometric methods. Two new books in the series explore the latest methods and tools in this rapidly growing area. A. Colin Cameron joins the distinguished panel of series editors that include Andrew Gelman, J. Scott Long, Sophia Rabe-Hesketh, and Anders Skrondal. Dr. Cameron is a professor in the Department of Economics at the University of California, Davis and has served as the Director of the U.C. Davis Center on Quantitative Social Science Research.
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations (2009), by Stanley A. Mulaik, integrates a general philosophical theory of causation with structural equation modeling that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. In Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences (2009) Brian S. Everitt goes beyond the usual coverage of hypothesis testing to provide a full explanation of the most useful methods for comparing and examining data in psychology, the social sciences, and law. He includes real data sets that provide a sampling of the issues commonly encountered when applying statistics in practice. In partnership with Stata Press, Chapman Hall/CRC offers Microeconometrics Using Stata (2009), co-authored by A. Colin Cameron and Pravin K. Trivedi, provides an outstanding introduction to microeconometrics and microeconometric research using Stata. Cameron and Trivedi cover specialized topics often left out of microeconometrics texts and basic introductions to Stata. They address each topic with an in-depth Stata example and demonstrate how to use Stata’s programming features to implement methods for which Stata does not have a specific command. Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Rounding out the collection, Introduction to Spatial Econometrics (January 2009), presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. James LeSage and R. Kelley Pace explore recent advances in spatial econometric models—including some previously unpublished results.
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Joint Statistical Meetings 2009
JSM 2009 – A Behind the Scenes Look It was several weeks before JSM 2007 when I got the email – “Was I interested in being the JSM 2009 Program Chair?” I immediately replied with a resounding YES! My name and others were then submitted as potential chairs to the Committee on Meetings. The committee chose me as the 2009 Program Chair, and my election was subsequently approved by Sally Morton, our current ASA President, and the ASA Executive Board. One of my first tasks in late 2007 was to appoint two General Wendy L. Martinez JSM 2009 Methods Chairs and the Poster Chair. These folks are very Program Chair important members of the program committee because they help me in many ways, such as with organizing the program, filling in for other committee members, and more. The remaining members of the program committee are either appointed by a member society (e.g., IMS, SSC, etc.) or elected by their section. Around this same time, ASA President Morton picked the theme for our meeting, and she chose an exciting one – Statistics: From Evidence to Policy. While sessions do not have to address it, the theme is very important, as it tends to drive the content of the invited and topic-contributed sessions. To gain experience in the process, the JSM 2009 Program Committee had to arrange some events for the previous year’s program. For example, the committee was responsible for organizing and scheduling the roundtable coffees and lunches for the 2008 meetings. We also started working on the invited program during this same time period – one year before our JSM! Then, the hard (but exciting and fun!) work begins. The partner societies, the ASA sections, and other entities have a certain number of invited sessions allocated to them. The appropriate committee members can organize the sessions or solicit ideas from their members. The representatives for the ASA sections, committees, and interest groups are allowed to submit two invited sessions for the competition slots, and the entire program committee votes on the ones they think should be included in the program. This was certainly a challenging and important part of the process because the invited sessions are the backbone of the meetings. JSM 2009 - Washington, DC From Evidence to Policy
Summer 2009
story continued on pg. 7 (JSM 2009)
Visit Chapman & Hall/CRC at Booth 304 Every year at JSM Chapman & Hall/ CRC offers attendees the chance to save on the best statistics books available. This year is no exception. You can build your library without breaking your bank. Save 50% on these classic books: Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Julian J. Faraway Handbook of Statistical Distributions with Applications, K. Krishnamoorthy Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Youngjo Lee, John A. Nedler, and Yudi Pawitan R Graphics, Paul Murrell Handbook of Parametric and Nonparametric Statistical Procedures, David J. Sheskin Linear Mixed Models: A Practical Guide Using Statistical Software, Brady West, Kathleen B. Welch, and Andrzej T. Galecki Generalized Additive Models: An Introduction with R, Simon Wood
The More You Buy, The More You Save In addition to these books, our regular conference-tiered discounts are available on any book you purchase. Save 15% on one, 20% on two, or 25% on three and more.
Drawings Held Daily Come by our booth on Monday or Tuesday and enter to win one of the $100 gift certificates. Come by on Wednesday for the chance to win a $300 gift certificate.
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JSM HIGHLIGHTS
SATURDAY, AUGUST 1 Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis - Continuing Education Course CE_02C ! Michael J. Daniels and Joseph W. Hogan authors of Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis teach this course.
SUNDAY, AUGUST 2 Tolerance Intervals: Theory, Applications, and Computation - Continuing Education Course CE_10C ! Presented by Kalimuthu Krishnamoorthy, author of Handbook of Statistical Distributions with Applications with Thomas Mathew. Hierarchical Modeling and Analysis of Spatial-Temporal Data: Emphasis in Forestry, Ecology, and Environmental Sciences - Continuing Education Course CE_12C ! Sudipto Banerjee and Andrew Finley give a short course based on Banerjee’s book: Hierarchical Modeling and Analysis for Spatial Data. Recent Advances in Bayesian Model Selection Invited Papers 3 ! David Madigan, editor of the Computer Science and Data Analysis series, discusses Sequential Bayesian Model Selection. Introductory Overview Lecture: Largely About Largeness: Models And Views For High-Dimensional Data 41 ! Organized by Wendy Martinez, co-author of the forthcoming Exploratory Data Analysis with MATLAB, Second Edition. The Issue of High Dimensionality and Missing Data in Complex Epidemiological Studies Invited Papers 46 ! Nicholas P. Jewell, author of Statistics for Epidemiology, presents Estimating and Ranking the Impact of High-Dimensional Environmental Risk Factors In Environmental Epidemiology.
MONDAY, AUGUST 3 Dose Finding Studies: Methods and Implementation - Continuing Education Course CE_16C ! Frank Bretz, co-author of Multiple Comparisons Using R teaches this course with Jose C. Pinheiro. IMS Medallion Lecture II Invited Papers 96 ! Chaired by Marina Meila, co-editor of the Computer Science and Data Analysis series. Recent Advances in Missing Data and Causal Inference Invited Papers 131 ! Geert Molenberghs, co-author of Longitudinal Data Analysis discusses Every Missing Not At Ranom Model for Incomplete Data Has Got a Missing At Random Counterpart With Equal Fit. Joseph L. Schafer, author of Analysis of Incomplete Multivariate Data, offers Causal Modeling When the Treatment is a Latent Class. JASA, Theory and Methods Invited Session Invited Papers 140 ! Raymond J Carroll, co-author of Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition presents Prediction in Measurement Error Models with Aurore Delaigle. Jianqing Fan, co-editor of the Monographs on Statistics and Applied Probability series and Susan Schennah are discussants in this session.
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What’s News !!!
Recent Advances and the Future of Statistics Invited Papers 198 ! Brad Efron, co-author of An Introduction to the Bootstrap, examines The Future of Indirect Evidence.
TUESDAY, AUGUST 4 Monte Carlo and Bayesian Computation with R - Continuing Education Course CE_25C ! Maria Rizzo, author of Statistical Computing with R, instructs this course with James Albert. Comprehensive Data Analysis Using Interactive Statistical Graphics - Continuing Education Course CE_26C ! Martin Theus and Simon Urbanek present a short course based on their book Interactive Graphics for Data Analysis: Interactive Graphics for Data Analysis. Advances in Spatial and Spatio-Temporal Modeling Invited Papers 246 ! Christopher Wikle, co-editor of the Interdisciplinary Statistics series, presents A Class of Nonlinear Spatio-Temporal Dynamic Models. IMS Medallion Lecture IV Invited Papers 250 ! Chaired by Galin L. Jones, co-author of Handbook of Markov Chain Monte Carlo: Methods and Applications. Emerging Trends and Evidence in High-Dimensional "Omics" investigations Invited Papers 290 ! David B. Allison, co-editor of DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments, explores Biostatistics' Rise As an Empirical Science: Genomic Research as the Leavening Agent. Random Effect Specification/Misspecification in Spatial/Spatiotemporal Health Modeling Invited Papers 291 ! Organized by Andrew B. Lawson, author of Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology.
WEDNESDAY, AUGUST 5 Bayesian Methods in Medicine and Biology Invited Papers 448 ! Organized by Wesley O. Johnson, co-author of Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians. Statistics in Defense and National Security Roundtable with Lunch 487 ! Organized by Jeffrey L. Solka, co-author of Exploratory Data Analysis with MATLAB, Second Edition.
THURSDAY, AUGUST 6 Introductory Overview Lecture: Statistical Learning and Data Mining 535 ! David J. Hand, co-author of ROC Curves for Continuous Data, explores Statistical Learning and Data Mining. The Influence of Psychology, Cartography and Computer Science on the Design of Interactive Graphics for Spatial Statistical Data Invited Papers 540 ! Organized by Linda Williams Pickle, co-author of Visualizing Data Patterns with Micromaps with Daniel B. Carr. Carr presents Visualizing Patterns in Data with Micromaps in this session.
StatisticsNewS David J. Hand is a professor of statistics at Imperial College in London, where among his diverse areas of responsibility, he is chair of Statistical Methods in the Retail Financial Services Research Group. Dr. Hand serves as president of the Royal Statistical Society and is a Fellow of the British Academy. He has been a recipient of the Guy Medal of the Royal Statistical Society, the Royal Society Wolfson Research Merit Award, and the IEEE ICDM Research Contributions Award. He has published countless papers and more than 20 books, including the newly available ROC Curves for Continuous Data (May 2009), with coauthor Wojtek J. Krzanowski. He also launched the journal Statistics and Computing and served a term as editor of the Journal of the Royal Statistical Society, Series C. Dr. Hand’s broad research interests include multivariate statistics, classification methods, pattern detection, and the interface between statistics and computing. His influence and advice has led to improvements in organizations ranging from banks to pharmaceutical companies to governments.
Pioneers Plotting the Future A key member of the development team for the R and Omegahat projects, Paul Murrell is one of the foremost innovators of the R environment. Focusing his research on statistical computing and graphics, Dr. Murrell is the author of the bestselling R Graphics (2005) and the recently published Introduction to Data Technologies (February 2009). He is a senior lecturer at the University of Auckland. It was at Auckland that he came under the influence of Robert Gentleman and Ross Ihaka—the noted R & R team that originated the R environment—and found his path. “When I found myself writing my own plotting software to produce charts for a psychology project report, I took it as an indicator of where my interests really lay.” Currently, XML and its vast research potential has Dr. Murrell’s attention. As for the future of statistics, he says, “From a research perspective, developing software tools needs to be a recognized career path in statistics so that people consider it as an option and are rewarded for making that career choice. From an educational perspective, statistics curriculums need to formally address topics in statistical computing, so that people have the necessary skills to be able to engage in software research.” Those lucky enough to assist him or attend his lectures have ample opportunity to witness both those perspectives in practice.
JSM 2009 (continued from pg. 1) There are also several invited session categories that are cho- You probably realize by now that I had a lot of help putting sen at the discretion of the JSM Program Chair, such as ASA the program together, and I would like to take this opportujournals, outside societies, ASA committees, memorial ses- nity to acknowledge the help of many people. First, I would sions, and Introductory Overview Lectures. The General like to thank our ASA President, Sally Morton for her excelMethods Chairs and I also had some lent leadership and support. The JSM invited session slots that we could fill. Program Committee, the General I think that this is one of the important Thus, we could somewhat shape the challenges that all members of the program Methods Chairs, and the Poster Chair program via these selections. committee faced – organizing a balanced did the bulk of the work organizing the program and not letting our biases and program. In particular, our JSM Poster Most of the invited program was finalinterests motivate our choices. Chair, Lara Schmidt did an outstandized by December 2008, after which we ing job putting together and promoting turned our attention to the contributed program. Proposed invited sessions that did not make it on the poster sessions. We could not do anything without the wonprogram could be converted to topic contributed sessions. derful people at the ASA Meetings Department: Donna However, for the most part, the JSM Program Committee just Arrington, Kathleen Wert, and Steve Porzio. I want to say a had to wait for contributed abstracts to roll in, which they did. special thank you to Donna, who was responsible for the JSM We received approximately 500 more abstracts (on average) technical program. She was always helpful, cheerful, and than the previous two meetings! Needless to say, this present- patient with our many questions and issues. Of course, the ed some significant scheduling challenges to the ASA JSM could not happen without the participation of the preMeetings Department and the JSM Program Committee, and senters, chairs, organizers, exhibitors, and all attendees – so everyone did a great job handling these and many other issues. thank you for making this JSM an event to remember!
7
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Introducing New Design & Analysis Software Bundles for Pharmaceutical R&D From Chapman & Hall/CRC & PharmaSoftware Solutions, Inc. Sample Size Calculations in Clinical Research, Second Edition & N Solution 2007 Basic The Book: This second edition of a bestselling reference features new chapters on dose finding, microarray studies, and Bayesian approaches. The Software enables quick and easy sample size calculation and power analysis. It contains all the procedures for testing equality, superiority/non-inferiority and equivalence for comparing means, proportions, and time-to-event data. In addition, sensitivity analyses for each procedure are also included. Catalog no. K10700, $249.95 / £132.00
Design and Analysis of Bioavailability and Bioequivalence Studies, Third Edition & BABE Solution 2008 Basic The Book: This edition of a bestseller features four new chapters that present a thorough account of novel developments in the field. The Software, based on the book, is the first devoted to the design and analysis of Bioavailability/Bioequivalence and features BE assessment of in vivo Bioequivalence studies. Catalog no. K10699, $299.95 / £167.00
Statistical Genetics (continued from pg. 3) One of the best tools for gene expression studies is the Keeping abreast of the ever-changing landscape of human genetics, CRC resources continue to Affymetrix GeneChip®. This explore the latest cutting-edge research that platform is the most broadly can make a difference in the lives of many. adopted single-color technology used in academic labs, clinics, and commercial entities. Gene Expression Studies Using Affymetrix Microarrays (CRC Press, June 2009) provides a detailed and systematic introduction as well as a practical user’s guide to this promising technology, including the use of R and other software for microarray analysis. The text also includes a wealth of information and key terminology regarding microarray gene expression studies in general.
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Taylor & Francis Journals — online and in print
Blurring the Line Between Users and Developers
Communications in Statistics: Simulation and Computation and Communications in Statistics: Theory and Methods includes papers on advance theory and methods in the computational aspects of Probability and Statistics. This pair of related journals, edited by N. Balakrishnan, presents formulation and discussion of problems as well as solutions in all areas of statistics, including graphic methods, resampling, and computationally intensive methods. In addition, the journals provide exhaustive coverage and up-to-date reviews of key topics by publishing special issues.
By now, most statisticians recognize R as one of the most flexible, integrated software environments for statistical computing and graphics. Its exceptional capacity for adaptability and its sophisticated presentation features make it the first choice of experienced statisticians as well as researchers with minimal formal training in statistical software. Chapman & Hall/CRC Press offers an array of books to help readers at various levels understand R and make use of its wide range of applications.
Sequential Analysis, edited by Nitis Mukhopadhyay, contributes to theoretical and applied aspects of sequential and applied methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches, and interdisciplinary articles emphasize the methodology of practical value to applied researchers and statistical consultants.
Best Paper Award 2008 from Journal of Nonparametric Statistics The Journal of Nonparametric Statistics and the ASA Section on Nonparametric Statistics are pleased to give the Best Paper Award in 2008 to P.L. Davies and M. Meise for their paper Approximating data with weighted smoothing splines published in Journal of Nonparametric Statistics Volume 20, Number 3, April 2008, 207-228. This paper will be FREE to view online in 2009. To access the paper and for further information about these and other journals, please visit: www.tandf.co.uk/journals.
Frontiers Harnessing the Power of Computing
Are you tapping into all that R offers?
Statistical Genetics: Operating at the intersection of human genetics and the mathematical sciences The analysis of genetic data has become a science unto itself, with statisticians taking on a critical role. Three new titles from CRC Press capture the state of the science in this fascinating field.
Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition (August 2009) continues to offer straightforward descriptions of how to use R and interpret the results. Authors Brian S. Everitt and Torsten Hothorn include new chapters on graphical displays, generalized additive models, and simultaneous inference, as well as a new section on generalized linear mixed models. In SAS and R: Data Management, Statistical Analysis, and Graphics (July 2009), Ken Kleinman and Nicholas J. Horton present an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. Introduction to Data Technologies (March 2009), written by R guru Paul Murrell, a member of the R Development Core Team, provides important information on how to work with research data. Murrell devotes separate chapters to each computer language, including R. “One of the core features of the R environment, which it inherited from S, is that there is a deliberate blurring of the distinction between users and developers. The system encourages and facilitates the development of new functionality. …new developments in research are implemented in software and communicated between researchers much more rapidly than ever before.” —Paul Murrell
Hidden Markov Models for Time Series: An Introduction Using R (April 2009), authored by Walter Zucchini and Iain L. MacDonald demonstrates how to apply HMMs to a wide range of time series types and discusses how to employ R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting. In Computational Statistics: An Introduction to R (January 2009), Günther Sawitzki also illustrates how R can be employed to tackle statistical problems. Unlike most guides to R, Introduction to Scientific Programming and Simulation Using R (March 2009) by Owen Jones, Robert Maillardet, and Andrew Robinson does not focus on the application of statistical techniques, but rather shows how to turn algorithms into code. This introductory book surveys a range of useful mathematical tools that either require or are illuminated by scientific computation. Another introductory text, An Introduction to Statistical Inference and Its Applications with R (June 2009) by Michael W. Trosset, explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. Most of these books offer code and supplemental material online. For more details about any of these, or other related works, please visit www.crcpress.com.
Focusing on problems arising in the analysis of genetics and genomics, Statistics in Human Genetics and Molecular Biology (July 2009) provides a graduate textbook of statistical methods used in genetics. Author Cavan Reilly covers cluster analysis, combinatorial optimization, and dynamic programming, along with the core topics of genome mapping, biological sequence analysis, and the analysis of gene expression arrays. He also explores Bayesian approaches, such as hidden Markov models and black motif methods, along with modern tools of Bayesian analysis, including Markov chain Monte Carlo (MCMC). With the diversity of data and metadata now available, there is increased interest in analyzing multiple studies beyond statistical approaches of formal meta-analysis. Meta-analysis and Combining Information in Genetics and Genomics (July 2009) is the first book devoted to meta-analysis in genetics. Addressing the complications inherent in comparing and replicating genetic studies, leading experts consider microarrays, gene mapping, and proteomics while detailing the various techniques used to analyze and combine data from different types of studies. story continued on pg. 6 (Statistical Genetics)
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Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA and Arizona State University, Tempe, USA
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Introduction to Data Technologies The University of Auckland, New Zealand
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Design and Analysis of Clinical Trials with Time-to-Event Endpoints Edited by
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Sample Sizes for Clinical Trials
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Data Management, Statistical Analysis, and Graphics
Data and Safety Monitoring Committees in Clinical Trials
Design and Analysis of Bioavailability and Bioequivalence Studies
Paul Murrell
King's College, University of London, UK
SAS and R
BioStatistics
University of Melbourne, Parkville, Australia
Second Edition
Nicholas. J Horton
Imperial College, London, UK
Owen Jones, Robert Maillardet, and Andrew Robinson
King's College, University of London, UK
Harvard Medical School, Boston, Massachusetts, USA
David J. Hand
4
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University of Exeter, UK
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Reading Beyond the Normal Distribution
Steven A. Julious
University of Sheffield, UK
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Meta-analysis and Combining Information in Genetics and Genomics Edited by
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Rice University, Houston, Texas, USA
Darlene R. Goldstein
EPFL SB IMA STAT, Switzerland
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Statistics in Human Genetics and Molecular Biology Cavan Reilly
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Gene Expression Studies Using Affymetrix Microarrays Hinrich Gohlmann and Willem Talloen Johnson & Johnson, Beerse, Belgium
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Partners in Publishing Scaling New Heights Through Synergy
Introducing New Design & Analysis Software Bundles for Pharmaceutical R&D From Chapman & Hall/CRC & PharmaSoftware Solutions, Inc. Sample Size Calculations in Clinical Research, Second Edition & N Solution 2007 Basic The Book: This second edition of a bestselling reference features new chapters on dose finding, microarray studies, and Bayesian approaches. The Software enables quick and easy sample size calculation and power analysis. It contains all the procedures for testing equality, superiority/non-inferiority and equivalence for comparing means, proportions, and time-to-event data. In addition, sensitivity analyses for each procedure are also included. Catalog no. K10700, $249.95 / £132.00
Design and Analysis of Bioavailability and Bioequivalence Studies, Third Edition & BABE Solution 2008 Basic The Book: This edition of a bestseller features four new chapters that present a thorough account of novel developments in the field. The Software, based on the book, is the first devoted to the design and analysis of Bioavailability/Bioequivalence and features BE assessment of in vivo Bioequivalence studies. Catalog no. K10699, $299.95 / £167.00
Statistical Genetics (continued from pg. 3) One of the best tools for gene expression studies is the Keeping abreast of the ever-changing landscape of human genetics, CRC resources continue to Affymetrix GeneChip®. This explore the latest cutting-edge research that platform is the most broadly can make a difference in the lives of many. adopted single-color technology used in academic labs, clinics, and commercial entities. Gene Expression Studies Using Affymetrix Microarrays (CRC Press, June 2009) provides a detailed and systematic introduction as well as a practical user’s guide to this promising technology, including the use of R and other software for microarray analysis. The text also includes a wealth of information and key terminology regarding microarray gene expression studies in general.
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Taylor & Francis Journals — online and in print
Blurring the Line Between Users and Developers
Communications in Statistics: Simulation and Computation and Communications in Statistics: Theory and Methods includes papers on advance theory and methods in the computational aspects of Probability and Statistics. This pair of related journals, edited by N. Balakrishnan, presents formulation and discussion of problems as well as solutions in all areas of statistics, including graphic methods, resampling, and computationally intensive methods. In addition, the journals provide exhaustive coverage and up-to-date reviews of key topics by publishing special issues.
By now, most statisticians recognize R as one of the most flexible, integrated software environments for statistical computing and graphics. Its exceptional capacity for adaptability and its sophisticated presentation features make it the first choice of experienced statisticians as well as researchers with minimal formal training in statistical software. Chapman & Hall/CRC Press offers an array of books to help readers at various levels understand R and make use of its wide range of applications.
Sequential Analysis, edited by Nitis Mukhopadhyay, contributes to theoretical and applied aspects of sequential and applied methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches, and interdisciplinary articles emphasize the methodology of practical value to applied researchers and statistical consultants.
Best Paper Award 2008 from Journal of Nonparametric Statistics The Journal of Nonparametric Statistics and the ASA Section on Nonparametric Statistics are pleased to give the Best Paper Award in 2008 to P.L. Davies and M. Meise for their paper Approximating data with weighted smoothing splines published in Journal of Nonparametric Statistics Volume 20, Number 3, April 2008, 207-228. This paper will be FREE to view online in 2009. To access the paper and for further information about these and other journals, please visit: www.tandf.co.uk/journals.
Frontiers Harnessing the Power of Computing
Are you tapping into all that R offers?
Statistical Genetics: Operating at the intersection of human genetics and the mathematical sciences The analysis of genetic data has become a science unto itself, with statisticians taking on a critical role. Three new titles from CRC Press capture the state of the science in this fascinating field.
Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition (August 2009) continues to offer straightforward descriptions of how to use R and interpret the results. Authors Brian S. Everitt and Torsten Hothorn include new chapters on graphical displays, generalized additive models, and simultaneous inference, as well as a new section on generalized linear mixed models. In SAS and R: Data Management, Statistical Analysis, and Graphics (July 2009), Ken Kleinman and Nicholas J. Horton present an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. Introduction to Data Technologies (March 2009), written by R guru Paul Murrell, a member of the R Development Core Team, provides important information on how to work with research data. Murrell devotes separate chapters to each computer language, including R. “One of the core features of the R environment, which it inherited from S, is that there is a deliberate blurring of the distinction between users and developers. The system encourages and facilitates the development of new functionality. …new developments in research are implemented in software and communicated between researchers much more rapidly than ever before.” —Paul Murrell
Hidden Markov Models for Time Series: An Introduction Using R (April 2009), authored by Walter Zucchini and Iain L. MacDonald demonstrates how to apply HMMs to a wide range of time series types and discusses how to employ R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting. In Computational Statistics: An Introduction to R (January 2009), Günther Sawitzki also illustrates how R can be employed to tackle statistical problems. Unlike most guides to R, Introduction to Scientific Programming and Simulation Using R (March 2009) by Owen Jones, Robert Maillardet, and Andrew Robinson does not focus on the application of statistical techniques, but rather shows how to turn algorithms into code. This introductory book surveys a range of useful mathematical tools that either require or are illuminated by scientific computation. Another introductory text, An Introduction to Statistical Inference and Its Applications with R (June 2009) by Michael W. Trosset, explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. Most of these books offer code and supplemental material online. For more details about any of these, or other related works, please visit www.crcpress.com.
Focusing on problems arising in the analysis of genetics and genomics, Statistics in Human Genetics and Molecular Biology (July 2009) provides a graduate textbook of statistical methods used in genetics. Author Cavan Reilly covers cluster analysis, combinatorial optimization, and dynamic programming, along with the core topics of genome mapping, biological sequence analysis, and the analysis of gene expression arrays. He also explores Bayesian approaches, such as hidden Markov models and black motif methods, along with modern tools of Bayesian analysis, including Markov chain Monte Carlo (MCMC). With the diversity of data and metadata now available, there is increased interest in analyzing multiple studies beyond statistical approaches of formal meta-analysis. Meta-analysis and Combining Information in Genetics and Genomics (July 2009) is the first book devoted to meta-analysis in genetics. Addressing the complications inherent in comparing and replicating genetic studies, leading experts consider microarrays, gene mapping, and proteomics while detailing the various techniques used to analyze and combine data from different types of studies. story continued on pg. 6 (Statistical Genetics)
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JSM HIGHLIGHTS
SATURDAY, AUGUST 1 Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis - Continuing Education Course CE_02C ! Michael J. Daniels and Joseph W. Hogan authors of Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis teach this course.
SUNDAY, AUGUST 2 Tolerance Intervals: Theory, Applications, and Computation - Continuing Education Course CE_10C ! Presented by Kalimuthu Krishnamoorthy, author of Handbook of Statistical Distributions with Applications with Thomas Mathew. Hierarchical Modeling and Analysis of Spatial-Temporal Data: Emphasis in Forestry, Ecology, and Environmental Sciences - Continuing Education Course CE_12C ! Sudipto Banerjee and Andrew Finley give a short course based on Banerjee’s book: Hierarchical Modeling and Analysis for Spatial Data. Recent Advances in Bayesian Model Selection Invited Papers 3 ! David Madigan, editor of the Computer Science and Data Analysis series, discusses Sequential Bayesian Model Selection. Introductory Overview Lecture: Largely About Largeness: Models And Views For High-Dimensional Data 41 ! Organized by Wendy Martinez, co-author of the forthcoming Exploratory Data Analysis with MATLAB, Second Edition. The Issue of High Dimensionality and Missing Data in Complex Epidemiological Studies Invited Papers 46 ! Nicholas P. Jewell, author of Statistics for Epidemiology, presents Estimating and Ranking the Impact of High-Dimensional Environmental Risk Factors In Environmental Epidemiology.
MONDAY, AUGUST 3 Dose Finding Studies: Methods and Implementation - Continuing Education Course CE_16C ! Frank Bretz, co-author of Multiple Comparisons Using R teaches this course with Jose C. Pinheiro. IMS Medallion Lecture II Invited Papers 96 ! Chaired by Marina Meila, co-editor of the Computer Science and Data Analysis series. Recent Advances in Missing Data and Causal Inference Invited Papers 131 ! Geert Molenberghs, co-author of Longitudinal Data Analysis discusses Every Missing Not At Ranom Model for Incomplete Data Has Got a Missing At Random Counterpart With Equal Fit. Joseph L. Schafer, author of Analysis of Incomplete Multivariate Data, offers Causal Modeling When the Treatment is a Latent Class. JASA, Theory and Methods Invited Session Invited Papers 140 ! Raymond J Carroll, co-author of Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition presents Prediction in Measurement Error Models with Aurore Delaigle. Jianqing Fan, co-editor of the Monographs on Statistics and Applied Probability series and Susan Schennah are discussants in this session.
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What’s News !!!
Recent Advances and the Future of Statistics Invited Papers 198 ! Brad Efron, co-author of An Introduction to the Bootstrap, examines The Future of Indirect Evidence.
TUESDAY, AUGUST 4 Monte Carlo and Bayesian Computation with R - Continuing Education Course CE_25C ! Maria Rizzo, author of Statistical Computing with R, instructs this course with James Albert. Comprehensive Data Analysis Using Interactive Statistical Graphics - Continuing Education Course CE_26C ! Martin Theus and Simon Urbanek present a short course based on their book Interactive Graphics for Data Analysis: Interactive Graphics for Data Analysis. Advances in Spatial and Spatio-Temporal Modeling Invited Papers 246 ! Christopher Wikle, co-editor of the Interdisciplinary Statistics series, presents A Class of Nonlinear Spatio-Temporal Dynamic Models. IMS Medallion Lecture IV Invited Papers 250 ! Chaired by Galin L. Jones, co-author of Handbook of Markov Chain Monte Carlo: Methods and Applications. Emerging Trends and Evidence in High-Dimensional "Omics" investigations Invited Papers 290 ! David B. Allison, co-editor of DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments, explores Biostatistics' Rise As an Empirical Science: Genomic Research as the Leavening Agent. Random Effect Specification/Misspecification in Spatial/Spatiotemporal Health Modeling Invited Papers 291 ! Organized by Andrew B. Lawson, author of Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology.
WEDNESDAY, AUGUST 5 Bayesian Methods in Medicine and Biology Invited Papers 448 ! Organized by Wesley O. Johnson, co-author of Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians. Statistics in Defense and National Security Roundtable with Lunch 487 ! Organized by Jeffrey L. Solka, co-author of Exploratory Data Analysis with MATLAB, Second Edition.
THURSDAY, AUGUST 6 Introductory Overview Lecture: Statistical Learning and Data Mining 535 ! David J. Hand, co-author of ROC Curves for Continuous Data, explores Statistical Learning and Data Mining. The Influence of Psychology, Cartography and Computer Science on the Design of Interactive Graphics for Spatial Statistical Data Invited Papers 540 ! Organized by Linda Williams Pickle, co-author of Visualizing Data Patterns with Micromaps with Daniel B. Carr. Carr presents Visualizing Patterns in Data with Micromaps in this session.
StatisticsNewS David J. Hand is a professor of statistics at Imperial College in London, where among his diverse areas of responsibility, he is chair of Statistical Methods in the Retail Financial Services Research Group. Dr. Hand serves as president of the Royal Statistical Society and is a Fellow of the British Academy. He has been a recipient of the Guy Medal of the Royal Statistical Society, the Royal Society Wolfson Research Merit Award, and the IEEE ICDM Research Contributions Award. He has published countless papers and more than 20 books, including the newly available ROC Curves for Continuous Data (May 2009), with coauthor Wojtek J. Krzanowski. He also launched the journal Statistics and Computing and served a term as editor of the Journal of the Royal Statistical Society, Series C. Dr. Hand’s broad research interests include multivariate statistics, classification methods, pattern detection, and the interface between statistics and computing. His influence and advice has led to improvements in organizations ranging from banks to pharmaceutical companies to governments.
Pioneers Plotting the Future A key member of the development team for the R and Omegahat projects, Paul Murrell is one of the foremost innovators of the R environment. Focusing his research on statistical computing and graphics, Dr. Murrell is the author of the bestselling R Graphics (2005) and the recently published Introduction to Data Technologies (February 2009). He is a senior lecturer at the University of Auckland. It was at Auckland that he came under the influence of Robert Gentleman and Ross Ihaka—the noted R & R team that originated the R environment—and found his path. “When I found myself writing my own plotting software to produce charts for a psychology project report, I took it as an indicator of where my interests really lay.” Currently, XML and its vast research potential has Dr. Murrell’s attention. As for the future of statistics, he says, “From a research perspective, developing software tools needs to be a recognized career path in statistics so that people consider it as an option and are rewarded for making that career choice. From an educational perspective, statistics curriculums need to formally address topics in statistical computing, so that people have the necessary skills to be able to engage in software research.” Those lucky enough to assist him or attend his lectures have ample opportunity to witness both those perspectives in practice.
JSM 2009 (continued from pg. 1) There are also several invited session categories that are cho- You probably realize by now that I had a lot of help putting sen at the discretion of the JSM Program Chair, such as ASA the program together, and I would like to take this opportujournals, outside societies, ASA committees, memorial ses- nity to acknowledge the help of many people. First, I would sions, and Introductory Overview Lectures. The General like to thank our ASA President, Sally Morton for her excelMethods Chairs and I also had some lent leadership and support. The JSM invited session slots that we could fill. Program Committee, the General I think that this is one of the important Thus, we could somewhat shape the challenges that all members of the program Methods Chairs, and the Poster Chair program via these selections. committee faced – organizing a balanced did the bulk of the work organizing the program and not letting our biases and program. In particular, our JSM Poster Most of the invited program was finalinterests motivate our choices. Chair, Lara Schmidt did an outstandized by December 2008, after which we ing job putting together and promoting turned our attention to the contributed program. Proposed invited sessions that did not make it on the poster sessions. We could not do anything without the wonprogram could be converted to topic contributed sessions. derful people at the ASA Meetings Department: Donna However, for the most part, the JSM Program Committee just Arrington, Kathleen Wert, and Steve Porzio. I want to say a had to wait for contributed abstracts to roll in, which they did. special thank you to Donna, who was responsible for the JSM We received approximately 500 more abstracts (on average) technical program. She was always helpful, cheerful, and than the previous two meetings! Needless to say, this present- patient with our many questions and issues. Of course, the ed some significant scheduling challenges to the ASA JSM could not happen without the participation of the preMeetings Department and the JSM Program Committee, and senters, chairs, organizers, exhibitors, and all attendees – so everyone did a great job handling these and many other issues. thank you for making this JSM an event to remember!
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StatisticsNewS Fit linear models without intercepts in SAS or R Routines for linear models in SAS and R incorporate an intercept by default. But, what's the syntax for fitting a model without an intercept? This entry from SAS and R: Data Management, Statistical Analysis, and Graphics (July 2009) will tell you. The book is designed as a bilingual SAS/R dictionary: If you know SAS, you can look up the noint option in the SAS index. If you know R, you can look up the 0 operator, or if you're unaware of how to do it in either, you can look up no intercept in the subject index.
SAS proc glm data=ds; model y = x1 ... xk / noint; run; Note: The noint option works with many model statements.
R mod1 < –lm(y ~ 0 + x1 + ... + xk, data=ds) or mod1 < –lm(y ~ x1 + ... + xk –1, data=ds)
Nexus
Making the Most Out of those Complex Datasets in the Social and Behavioral Sciences Large and complex datasets are becoming increasingly prevalent in the social and behavioral sciences. The Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series makes the lives of statisticians working in the applied sciences easier by exploring the effective and efficient use of statistical, econometric, and psychometric methods. Two new books in the series explore the latest methods and tools in this rapidly growing area. A. Colin Cameron joins the distinguished panel of series editors that include Andrew Gelman, J. Scott Long, Sophia Rabe-Hesketh, and Anders Skrondal. Dr. Cameron is a professor in the Department of Economics at the University of California, Davis and has served as the Director of the U.C. Davis Center on Quantitative Social Science Research.
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations (2009), by Stanley A. Mulaik, integrates a general philosophical theory of causation with structural equation modeling that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. In Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences (2009) Brian S. Everitt goes beyond the usual coverage of hypothesis testing to provide a full explanation of the most useful methods for comparing and examining data in psychology, the social sciences, and law. He includes real data sets that provide a sampling of the issues commonly encountered when applying statistics in practice. In partnership with Stata Press, Chapman Hall/CRC offers Microeconometrics Using Stata (2009), co-authored by A. Colin Cameron and Pravin K. Trivedi, provides an outstanding introduction to microeconometrics and microeconometric research using Stata. Cameron and Trivedi cover specialized topics often left out of microeconometrics texts and basic introductions to Stata. They address each topic with an in-depth Stata example and demonstrate how to use Stata’s programming features to implement methods for which Stata does not have a specific command. Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Rounding out the collection, Introduction to Spatial Econometrics (January 2009), presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. James LeSage and R. Kelley Pace explore recent advances in spatial econometric models—including some previously unpublished results.
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Joint Statistical Meetings 2009
JSM 2009 – A Behind the Scenes Look It was several weeks before JSM 2007 when I got the email – “Was I interested in being the JSM 2009 Program Chair?” I immediately replied with a resounding YES! My name and others were then submitted as potential chairs to the Committee on Meetings. The committee chose me as the 2009 Program Chair, and my election was subsequently approved by Sally Morton, our current ASA President, and the ASA Executive Board. One of my first tasks in late 2007 was to appoint two General Wendy L. Martinez JSM 2009 Methods Chairs and the Poster Chair. These folks are very Program Chair important members of the program committee because they help me in many ways, such as with organizing the program, filling in for other committee members, and more. The remaining members of the program committee are either appointed by a member society (e.g., IMS, SSC, etc.) or elected by their section. Around this same time, ASA President Morton picked the theme for our meeting, and she chose an exciting one – Statistics: From Evidence to Policy. While sessions do not have to address it, the theme is very important, as it tends to drive the content of the invited and topic-contributed sessions. To gain experience in the process, the JSM 2009 Program Committee had to arrange some events for the previous year’s program. For example, the committee was responsible for organizing and scheduling the roundtable coffees and lunches for the 2008 meetings. We also started working on the invited program during this same time period – one year before our JSM! Then, the hard (but exciting and fun!) work begins. The partner societies, the ASA sections, and other entities have a certain number of invited sessions allocated to them. The appropriate committee members can organize the sessions or solicit ideas from their members. The representatives for the ASA sections, committees, and interest groups are allowed to submit two invited sessions for the competition slots, and the entire program committee votes on the ones they think should be included in the program. This was certainly a challenging and important part of the process because the invited sessions are the backbone of the meetings. JSM 2009 - Washington, DC From Evidence to Policy
Summer 2009
story continued on pg. 7 (JSM 2009)
Visit Chapman & Hall/CRC at Booth 304 Every year at JSM Chapman & Hall/ CRC offers attendees the chance to save on the best statistics books available. This year is no exception. You can build your library without breaking your bank. Save 50% on these classic books: Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Julian J. Faraway Handbook of Statistical Distributions with Applications, K. Krishnamoorthy Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Youngjo Lee, John A. Nedler, and Yudi Pawitan R Graphics, Paul Murrell Handbook of Parametric and Nonparametric Statistical Procedures, David J. Sheskin Linear Mixed Models: A Practical Guide Using Statistical Software, Brady West, Kathleen B. Welch, and Andrzej T. Galecki Generalized Additive Models: An Introduction with R, Simon Wood
The More You Buy, The More You Save In addition to these books, our regular conference-tiered discounts are available on any book you purchase. Save 15% on one, 20% on two, or 25% on three and more.
Drawings Held Daily Come by our booth on Monday or Tuesday and enter to win one of the $100 gift certificates. Come by on Wednesday for the chance to win a $300 gift certificate.