Key Dates

  • January 27, 2014
    Deadline for special requests for abstract submission/registration for U.S. government agencies
  • July 2 - July 17, 2014
    Late Registration (increased fees apply)

Program > Add-Ons

JSM sessions which require ticket purchase have limited availability and therefore are subject to sell-out or cancellation. Below are the functions which still have availability. Although this list is updated in real-time, please bear in mind that tickets are sold online around the clock; if you plan to purchase a function ticket onsite and see the function on this list before you travel to JSM, we cannot guarantee it will still be available for purchase when you arrive at JSM. To find out how many tickets remain for a particular function, please contact the ASA at (703) 684-1221.

Available Add-Ons

Continuing Education and Computer Technology Workshops

CE_02C (HALF-DAY COURSE) Adaptive Tests of Significance Using R and SAS
Instructor(s): Tom O'Gorman

We will describe the two-sample adaptive test, present an adaptive method of testing any subset of coefficients in a multiple regression model and show how to perform the adaptive tests using R and SAS, discuss adaptive tests for interaction and main effects in the analysis of factorial experiments and adaptive tests for multicenter trial data, and describe a method of computing adaptive confidence intervals. Attendees should be at the level of Applied Regression Analysis (1998) by Draper and Smith.

CE_12C (HALF-DAY COURSE) A Statistician's Guide to Analyzing Unstructured Textual Data
Instructor(s): Goutam Chakraborty

This short course takes a quick look at how to collect, organize, and analyze textual data for extracting deeper insights into any research problem. The course will illustrate how such insights can be used to help businesses build better relationships with their customers. SAS products will be used as tools for demonstration; however, the topics and theories covered will be generic.

CE_14C Design and Analysis of Noninferiority Trials
Cosponsor: Biopharmaceutical Section

Instructor(s): Brian Wiens

*JSM 2012 Excellence-in-CE Award Winner
We will review the basics of noninferiority clinical trials and discuss advanced aspects. Participants should to have some experience with clinical trials aimed at regulatory approval for drugs, biologics, or medical devices.

CE_15C Nonparametric Bayesian Data Analysis
Cosponsor: Section on Bayesian Statistical Science

Instructor(s): Peter Mueller and Fernando Quintana

We will discuss the use of nonparametric Bayesian inference for a number of common statistical inference problems, including density estimation, regression, mixed effects models, classification, and clustering. Attendees should have working knowledge of Bayesian data anlysis and basic knowledge of Markov chain Monte Carlo posterior simulation.

CE_16C Missing Data Methods for Regression Modeling
Cosponsor: Biometrics Section

Instructor(s): Joseph Ibrahim

This short course will focus on regression models and research problems encountered in actual practice and demonstrate a variety of statistical packages dealing with missing data, including SAS, logXact, and WinBUGS.

CE_17C The Design and Analysis of Experiments That Use Computer Simulators
Cosponsor: Section on Physical and Engineering Sciences

Instructor(s): Thomas Santner and Brian J. Williams

This course will provide attendees with a set a tools for designing and analyzing studies that use computer simulators as experimental vehicles. It is based on the second edition of The Design and Analysis of Computer Experiments by Santner, Williams, and Notz.

CE_18C (HALF-DAY COURSE) Meta-Analysis: Combining the Results of Multiple Studies
Cosponsor: Health Policy Statistics Section

Instructor(s): Christopher Schmid and Ingram Olkin

In this workshop, we introduce the major principles and techniques of statistical analysis of meta-analytic data. Examples of published meta-analyses in medicine and the social sciences will be used to illustrate the various methods.

CE_19C (HALF-DAY COURSE) Regression Modeling with Many Correlated Predictors: Big Data in Practice
Instructor(s): Jay Magidson and Tony Babinec

In this course, we review problems and limitations with traditional linear and logistic regression, introduce and compare the two primary regularization approaches for analyzing such data, discuss related software, and introduce recent advances in feature selection.

CE_20C (HALF-DAY COURSE) Cure Models and their Applications
Cosponsor: Biometrics Section

Instructor(s): Jeremy Taylor and Yingwei Peng

This course will cover different types of cure models, their estimation methods, identifiability issues, software, and extensions to clustered data. The instructors will introduce real-life data sets from clinical studies and demonstrate the use of the cure models on the data with software.

CE_21C Modern Design of Factorial Experiments
Cosponsor: Section on Physical and Engineering Sciences

Instructor(s): Peter Goos and Bradley Jones

This course motivates the standard and routine use of a fully flexible approach to design of experiments-named optimal design of experiments-by showing its industrial application in 10 case studies covering a wide range of practical situations.

CE_22C Genomic Clinical Trials and Predictive Medicine
Cosponsor: Biopharmaceutical Section

Instructor(s): Richard Simon

This course will provide up-to-date information about the use of genomics in the design and analysis of therapeutic clinical trials with a focus on novel approaches that provide a reliable basis for "personalizing" treatment decisions.

CE_23C Bayesian Inference
Cosponsor: Section on Bayesian Statistical Science

Instructor(s): Bruno Sanso

This course reviews the bases of Bayesian inference, focusing on key general concepts rather than the technical detail of specific methods. Participants should have a good knowledge of statistics. Calculus and basic probability theory are considered a prerequisite.

CE_24C Causal Mediation Analysis
Cosponsor: Section on Statistics in Epidemiology

Instructor(s): Tyler VanderWeele

This course will cover recent developments in causal mediation analysis and provide practical tools to implement these techniques. Familiarity with linear and logistic regression are required to fully benefit from the course.

CE_25C (HALF-DAY COURSE) Interval-Censored Time-to-Event Data: Methods and Applications
Instructor(s): Tony Sun and Din Chen

This course provides a thorough presentation of statistical analyses of interval-censored failure time data with detailed illustrations using real data. It is partially based on Statistical Analysis of Interval-Censored Failure Time Data and Interval-Censored Time-to-Event Data: Methods and Applications.

CE_26C (HALF-DAY COURSE) Techniques for Simulating Data in SAS
Cosponsor: Section for Statistical Programmers and Analysts

Instructor(s): Rick Wicklin

*JSM 2013 Excellence-in-CE Award Winner
This workshop presents intermediate-level algorithms and techniques for simulating data from mixture distributions, multivariate distributions with a given correlation, distributions with arbitrary marginal distributions and correlation structure, distributions of correlation matrices, regression models with fixed and random effects, basic spatial models, and distributions with central moments that match the sample moments of real data.

CE_27T Introduction to Data Mining with CART Classification and Regression Trees
Instructor(s): Mikhail Golovnya

This workshop is intended for the applied statistician wanting to understand and apply the CART classification and regression trees methodology for tree-structured nonparametric data analysis. The emphasis will be on practical data analysis and data mining involving classification and regression. All attendees will receive six months' access to fully functional versions of the SPM Salford Predictive Modeler software suite.

CE_28T Creating Statistical and Clinical Graphics in SAS®
Instructor(s): Warren Kuhfeld

This workshop is intended for statistical users and covers the use of ODS Graphics from start to finish. No prior experience with ODS Graphics is assumed.

CE_29T Structural Equation Modeling Using Stata
Instructor(s): Kristin MacDonald

This workshop covers the use of Stata to perform structural equation modeling (SEM) and provides an overview of fitting linear structural equation models and evaluating model fit. No prior knowledge of Stata is required, but familiarity with SEM will prove useful.

CE_30T Modern Dose Escalation Designs for Oncology in East®
Instructor(s): Pantelis Vlachos and Charles Liu

East offers new capabilities to design, simulate, and execute Phase 1 oncology trials to determine the maximum-tolerated dose. In addition to the 3+3 design, the module includes modified Toxicity Probability Interval, Continual Reassessment, and Bayesian Logistic Regression models. We will review the theory for these methods and their application in East.

CE_31T Introduction to Modern Regression Analysis Techniques: Linear, Logistic, Nonlinear, Regularized, GPS, LARS, LASSO, Elastic Net, and MARS
Instructor(s): Mikhail Golovnya

This workshop will introduce the main concepts behind Jerome Friedman's GPS andMARS modern regression tools, which can help analysts quickly develop predictive models. All attendees will receive six months' access to fully functional versions of the SPM Salford Predictive Modeler software suite. Basic knowledge of classical and logistic regression is recommended.

CE_32T Model Selection Methods with Examples from SAS/STAT Software
Instructor(s): Funda Gunes

What subset of the effects provides the best model for the data? This workshop explains how you can address this question with modern model selection methods for linear and generalized linear models. We will focus on applications of the GLMSELECT procedure, but also feature the new HPGENSELECT procedure and HPREG procedures.

CE_33T Multilevel and Mixed Models in Stata
Instructor(s): Bill Rising

This workshop covers the use of Stata to fit multilevel (mixed) models. The focus will be on linear (Gaussian) models, but binary and count responses will be considered. No prior knowledge of Stata is required, but familiarity with the methodology and experience in fitting these models by other means will prove useful.

CE_34T Designing Confirmatory Trials with Multiple Endpoints in East® 6.3
Instructor(s): Cyrus Mehta and Lingyun Liu

We will look at two new simulation tools for designing and monitoring clinical trials: Trials with Multiple Endpoints and Predictive Interval Plots.

CE_35T Evolution of Classification: From Logistic Regression and Decision Trees to Bagging/Boosting and Netlift Modeling-Case Study Examples Drawn from Direct Marketing and Biomedical Data Analysis
Instructor(s): Mikhail Golovnya

We will discuss recent improvements to conventional decision tree and logistic regression technology via direct marketing and biomedical data analysis cse studies. This workshop will be especially interesting to those looking to better understand the newest advances in segmenting their databases and detecting subsets of populations. All attendees will receive six months' access to fully functional versions of the SPM Salford Predictive Modeler software suite.

CE_36T Current Methods in Survival Analysis Using SAS/STAT Software
Instructor(s): Changbin Guo

This workshop describes how to compute the nonparametric estimate of the cumulative incidence function and covers a SAS macro that implements it and provides tests for group comparison. In addition, we will discuss two approaches that are available with the PHREG procedure for evaluating the relationship of covariates to the cause-specific failure.

CE_37T Power and Sample-Size Analysis in Stata
Instructor(s): Yulia Marchenko

This workshop covers the use of Stata to perform power and sample-size analysis. No prior knowledge of Stata is required, but basic familiarity with power and sample-size analysis will prove useful.

CE_38T Applied Data Mining Analysis: A Step-by-Step Introduction Using Real-World Data Sets
Instructor(s): Mikhail Golovnya

This workshop follows a step-by-step approach to introduce advanced automation technology, including CART, MARS, TreeNet Gradient Boosting, Random Forests, and the latest multi-tree boosting and bagging methodologies by the original creators of CART. All attendees will receive six months' access to fully functional versions of the the SPM Salford Predictive Modeler software suite.

CE_39T Power and Sample Size Computations
Instructor(s): John Castelloe

We will review basic methodology for power and sample size computations for a number of analyses, including proportion tests, t-tests, confidence intervals, equivalence and noninferiority tests, survival analyses, correlation, regression, ANOVA, and more complex linear models. A basic understanding of power and sample size computations is assumed.

CE_40T Multiple Imputation Using Stata
Instructor(s): Yulia Marchenko

This workshop covers the use of Stata to perform multiple-imputation analysis. No prior knowledge of Stata is required, but basic familiarity with multiple imputation will prove useful.

CE_44P Strategic Career Management
Instructor(s): Janet Bickel

Targeted at the needs of early-career statisticians, this course introduces key career skill areas, supplementing what is obtainable from institutional career advising programs and mentors. It follows a highly interactive format, with brief presentations alternating with opportunities for reflection, pair work, small group discussion, and skills practice.

CE_45P Effective Presentations for Statisticians
Instructor(s): Jennifer van Mullekom and Bob Starbuck

This course will cover slide preparation, crafting an argument, oral presentations, and communicating statistical ideas. Attendees will review examples of effective presentation techniques, learn how to make effective presentations to different audience types using various platforms, and improve communication skills to both statisticians and nonstatisticians.

CE_46P From Idea to Publication: How to Get That Book Written
Instructor(s): James Ramsay and Maura Stokes

This interactive workshop provides a framework for making the decision to write a book and planning the writing and editing process. The first part focuses on book design, while the second part focuses on managing the writing process.

CE_47T Clinical Trial Simulation and Design Using the FACTS Platform
Instructor(s): Scott Berry and Ashish Sanil

The FACTS platform enables users to define and simulate a large class of trials that encompass a range of features including fixed and Bayesian adaptive designs with continuous, dichotomous, and time-to-event endpoints; clinical utility-based combination of multiple endpoints; enrichment designs; and dose-escalation. We will present examples to illustrate the process of designing a trial by iteratively simulating and exploring a range of designs using FACTS.

Monday Roundtables and Speaker Luncheons

ML03 What's It Like to Be a Statistician in the Physical and Engineering Sciences?
Sponsor: Section on Physical and Engineering Sciences

Instructor(s): Tena Katsaounis, Ohio State University

Join us for a discussion about SPES activities and programs. Tell us about your interests and find out how you can become an active member of SPES.

Fee for this session includes continental breakfast.

Tuesday Roundtables and Speaker Luncheons

Wednesday Roundtables and Speaker Luncheons

WL08 Statistical Issues in Process Validation of Pharmaceutical Products
Sponsor: Biopharmaceutical Section

Instructor(s): Katherine E. D. Giacoletti, McNeil Consumer Healthcare/Johnson & Johnson

This roundtable discussion is related to the contributed session on the same topic.

Fee for this session includes lunch.

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