JSM 2015 Preliminary Program

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Legend: Washington State Convention Center = CC, Sheraton Seattle = S, Grand Hyatt = GH and The Conference Center = TCC
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Activity Details

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CE_01C Sat, 8/8/2015, 8:30 AM - 5:00 PM S-Grand Ballroom C
(2-Day Course) Statistical Analysis with Missing Data (ADDED FEE) — Professional Development Continuing Education Course
ASA
This short course will discuss methods for the statistical analysis of data sets with missing values. Topics will include the definition of missing data; assumptions about mechanisms, including missing at random; pros and cons of simple methods such as complete-case analysis, naïve imputation, etc.; weighting methods; multiple imputation; maximum likelihood and Bayesian inference with missing data; computational techniques, including EM algorithm and extensions and Gibbs sampler; software for handling missing data; missing data in common statistical applications, including regression, repeated-measures analysis, and clinical trials; and selection and pattern-mixture models for nonrandom nonresponse. The course requires knowledge of standard statistical models such as the multivariate normal, multiple linear regression, and contingency tables, as well as matrix algebra, calculus, and basic maximum likelihood for common distributions. Recommended text: Little, R.J., and Rubin, D.B. (2002), Statistical Analysis with Missing Data, 2nd edition, Wiley.
Instructor(s): Roderick Little, University of Michigan, Trivellore Raghunathan, University of Michigan




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