Program > Online Program
Wed, Oct 5 |
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Conference Registration |
7:30 AM - 6:30 PM
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Workshop 1 Propensity Score Methods |
8:30 AM - 10:15 AM
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Organizer(s): Peter Austin, Institute for Clinical Evaluative Sciences, and University of Toronto, Canada |
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Propensity score methods are increasingly being used in health services and comparative effectiveness research to estimate the effects of treatments, interventions, and exposures on outcomes using observational or non-randomized data. We will begin by briefly reviewing the design and analysis of randomized controlled trials (RCTs). Participants will then be introduced to the concept of the propensity score and how it can be estimated using observational data. We will then examine how the propensity score can be used for matching, weighting, stratification, or covariate adjustment to estimate treatment effects. We will discuss how the first three of these methods allow one to mimic some of the characteristics of an RCT. We will also describe methods for assessing whether the propensity score model has been adequately specified using the observed data. |
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8:30 AM |
Propensity Score Methods for Estimating Treatment Effects Using Observational Data
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Workshop 5 (Part I) Introduction to Item Response Theory and Computerized Adaptive Testing for Outcomes Measurement Instruments (Part I) |
8:30 AM - 10:15 AM
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Organizer(s): Laura Lee Johnson, NIH |
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Research studies and clinicians increasingly collect self-reported health measures. However, the development and interpretation of the measurements are often overlooked. Many new patient reported outcome (PRO) instruments use modern measurement theory, offering advantages in instrument creation and application. Attendees will become familiar with basic item response theory (IRT) terminology, what it is, how it works, and how IRT compares to classical test theory. Speakers also will discuss the fundamentals of computer adaptive testing (CAT) and what is required to create and administer CAT. Key points and the challenges and opportunities for using PRO instruments in health policy research will be illustrated with examples. |
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8:30 AM |
Introduction to Item Response Theory and Computerized Adaptive Testing for Outcomes Measurement Instruments (Part I)
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Workshop 7 Quantile Regression |
8:30 AM - 10:15 AM
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Organizer(s): Brian Neelon, Duke University |
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Quantile regression seeks to provide a more complete picture of regression problems by analyzing all the conditional quantiles of the response in terms of interpretable linear models. This is especially useful when population heterogeneity leads to variation in the regression parameters as the quantile probability changes. The basic ideas will be presented through examples and the underlying basis for quantile regression will be summarized. Recent work on censored regression quantiles (for survival models) will be presented. |
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8:30 AM |
Quantile Regression
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Break |
10:15 AM - 10:30 AM
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Workshop 2 Estimating Treatment Effects Using Longitudinal Data |
10:30 AM - 12:15 PM
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Organizer(s): Miguel Hernan, Harvard School of Public Health |
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The availability and use of observational data---electronic medical records, claims databases, registries, etc.---is increasing in medical research. However, a valid estimation of the causal effects of treatment from observational data requires strong assumptions regarding confounding and other potential biases. Estimating the effects of time-varying treatments in the presence of time-varying confounding factors also requires the use of appropriate analytic methods. The goal of this workshop is to describe the implementation of several techniques for the estimation of causal treatment effects in longitudinal observational data. We will discuss the relative advantages and disadvantages of inverse probability weighting of marginal structural models and the parametric g-formula. |
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10:30 AM |
Estimating Treatment Effects Using Longitudinal Data
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Workshop 5 (Part II) Introduction to Item Response Theory and Computerized Adaptive Testing for Outcomes Measurement Instruments (Part II) |
10:30 AM - 12:15 PM
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Organizer(s): Laura Lee Johnson, NIH |
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Research studies and clinicians increasingly collect self-reported health measures. However, the development and interpretation of the measurements are often overlooked. Many new patient-reported outcome (PRO) instruments use modern measurement theory, offering advantages in instrument creation and application. Attendees will become familiar with basic item response theory (IRT) terminology, what it is, how it works, and how IRT compares to classical test theory. Speakers also will discuss the fundamentals of computerized adaptive testing (CAT) and what is required to create and administer CAT. Key points and a description of how PRO instruments can be used in health policy research will be illustrated. Examples of implementation problems focused on system integration, computer-based testing and CAT/IRT also will be discussed. |
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10:30 AM |
Introduction to Item Response Theory and Computerized Adaptive Testing for Outcomes Measurement Instruments (Part II)
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Workshop 8 Multiple Comparisons for Making Decisions |
10:30 AM - 12:15 PM
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Organizer(s): Bo Lu, The Ohio State University |
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This course is about using multiple comparisons to make decisions in clinical and genomic studies. We will discuss the construction of multiple tests using the fundamental principle of Partitioning, using Holm’s method and Hochberg’s method as examples. This will include subtle issues in the control of Family-wise Error Rate, generalized Family-wise Error Rate, and False Discovery Rate. Applications draw from studies involving bioequivalence, multiple endpoints, and personalized medicine. |
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10:30 AM |
Multiple Comparisons for Making Decisions
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Lunch on Your Own |
12:15 PM - 1:30 PM
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Workshop 3 Instrumental Variable Methods for Accounting for Selection and Survival Bias in Observational Studies |
1:30 PM - 3:15 PM
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Organizer(s): Therese A. Stukel, Institute for Clinical Evaluative Sciences and University of Toronto |
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Confounding frequently occurs in observational studies of the effects of treatments or exposures on health outcomes. While standard statistical methods can remove bias due to measured confounding, non-standard methods are required to remove bias due to unmeasured confounding. This workshop will address several statistical issues in estimating treatment effects when key confounders are unobserved or unobservable. Issues in the design and analysis of observational studies when estimating treatment effects using observational data will be highlighted. We will give an overview of analysis methods for removing confounding, including standard regression and propensity-based methods. We will introduce instrumental variable (IV) methods, providing an overview, properties, strength and validity of a proposed instrument, interpretation and analysis techniques. We will review examples of good and poor IV analyses in the health services literature, with an in-depth review of a study of the effects of invasive cardiac care on AMI mortality. Finally, we will assess which types of studies are more amenable to which techniques and will design a study of antipsychotic medications on patient mortality using varying techniques. |
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1:30 PM |
Instrumental Variable Methods for Accounting for Selection and Survival Bias in Observational Studies
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Workshop 6 (Part I) Interpreting Change and Responder Analyses for Patient-Responder Outcomes (Part I) |
1:30 PM - 3:15 PM
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Organizer(s): Joseph C. Cappelleri, Pfizer, Inc. |
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Patient-reported outcome (PRO) measures used for labeling and promotional claims must have: 1) evidence documenting their responsiveness; and 2) interpretation guidelines (e.g., responder definition) to be most useful as effectiveness endpoints in clinical trials. The recommended approach is to estimate the responder definition based on anchor-based methods, which will be discussed during the workshop. However, this workshop will also discuss how distribution-based methods can provide some insights on interpreting the amount of change that signifies an important change in PROs. Confidence in a specific responder change threshold evolves over time and is confirmed by additional research evidence, including clinical trial experience; the responder change threshold may vary by population and context, and no one responder change threshold will be valid for all study applications involving a PRO instrument. During this workshop, the speakers will explain how to demonstrate and identify thresholds for specific study populations in an effort to pursue labeling and promotional claims. |
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1:30 PM |
Interpreting Change and Responder Analyses for Patient-Responder Outcomes (Part I)
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Workshop 9 Network Meta-Analysis |
1:30 PM - 3:15 PM
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Organizer(s): Christopher Schmid, Tufts University Medical Center |
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This workshop will describe techniques for meta-analysis of data when it is desired to compare more than two treatments in a network. Emphasis will be on Bayesian models which allow for ranking of the comparative efficacy of treatments through calculation of the relevant posterior probabilities. Knowledge of the motivation for meta-analysis as well as basic statistical models for combining data of different types will be assumed. |
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1:30 PM |
Network Meta-Analysis
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Break |
3:15 PM - 3:30 PM
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Workshop 10 Evaluation of Diagnostic and Predictive Accuracy of Medical Tests and Biomarkers |
3:30 PM - 5:15 PM
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Organizer(s): Andrew Zhou, HSR&D Center of Excellence, VA Puget South Health Care System, and University of Washington |
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Diagnostic tests play a pivotal role in medicine, often determining what additional diagnostic tests, treatments, and interventions are needed and ultimately affecting patients' outcomes. This workshop provides a comprehensive approach to designing and analyzing diagnostic accuracy studies, so as to aid clinicians in understanding these studies and in generalizing study results to their patient populations. The basis for the course is the upcoming second edition of "Statistical Methods in Diagnostic Medicine", by Zhou, Obuchowski and McClish. We define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present statistical methods for estimating and comparing tests' accuracies, calculating sample size, and synthesizing the literature for meta-analysis. We then present more advanced statistical methods for describing a test's accuracy when accuracy is affected by patient characteristics, for analyzing multi-reader studies, for correcting for verification bias or imperfect gold standard bias, and for performing meta-analyses. The attendees are assumed to have a basic understanding of maximum likelihood and Bayesian methods as well as generalized linear models. |
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3:30 PM |
Evaluation of Diagnostic and Predictive Accuracy of Medical Tests and Biomarkers
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Workshop 4 Multiple Imputation Using Chained Equations (MICE) |
3:30 PM - 5:15 PM
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Organizer(s): Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health |
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This workshop will discuss multiple imputation using chained equations (MICE), a flexible procedure for creating multiple imputations to handle missing data. MICE can handle many data complexities, such as bounds and survey skip patterns, and can be implemented in large datasets. After providing a brief introduction to missing data and multiple imputation in general, this workshop will discuss the MICE method and provide references for software implementation. |
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3:30 PM |
Multiple Imputation Using Chained Equations (MICE)
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Workshop 6 (Part II) Interpreting Change and Responder Analyses for Patient-Responder Outcomes (Part II) |
3:30 PM - 5:15 PM
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Patient-reported outcome (PRO) measures used for labeling and promotional claims must have: 1) evidence documenting their responsiveness; and 2) interpretation guidelines (e.g., responder definition) to be most useful as effectiveness endpoints in clinical trials. The recommended approach is to estimate the responder definition based on anchor-based methods, which will be discussed during the workshop. However, this workshop will also discuss how distribution-based methods can provide some insights on interpreting the amount of change that signifies an important change in PROs. Confidence in a specific responder change threshold evolves over time and is confirmed by additional research evidence, including clinical trial experience; the responder change threshold may vary by population and context, and no one responder change threshold will be valid for all study applications involving a PRO instrument. During this workshop, the speakers will explain how to demonstrate and identify thresholds for specific study populations in an effort to pursue labeling and promotional claims. |
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3:30 PM |
Interpreting Change and Responder Analyses for Patient-Responder Outcomes (Part II)
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Poster Session I & Welcome Reception |
5:30 PM - 6:30 PM
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Teaching statistics in developing nations
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The impact of reference pricing system on brand name’s prices: the case of Tunisia
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A Comparison of Variable Importance Measures for Patient-Reported Outcomes
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Strategies for financing healthcare costs over the long term
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High frequency evidence on variation in spending growth
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A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits
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Exploratory Discriminant Analysis in Phase 2 Clinical Trials to investigate Treatment Effect Heterogeneity
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Policy implications resulting from connecting survival models to the underlying biological processes
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Sequential Testing for Intraclass Correlation Coefficient in Inter-Rater Reliability Studies
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Identifying predictors of cancer related quality of life using Bayesian model averaging (BMA)
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Assessing the sensitivity of net monetary benefits using non-linear models
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To balance or not to balance: a study of balancing propensity scores weighting and regression to assess the effect of being HIV positive on outcomes among heterosexually active homeless men
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How well does AIC perform in partially observed data?
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Assessing the privacy of randomized vector valued queries to a database using the area under the receiver-operator characteristic curve
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The Factors that Affect the Frequency of Vital Sign Monitoring During Times of Emergency Department Crowding
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Bivariate Spatial Analysis of Birth Weight and Gestational Age
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Split Sample Methods in Observational Studies with Choice of Multiple Hypotheses
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Optimal Designs in the N of 1 Trials
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How much compliance is enough? Estimating the Complier Average Causal Effect (CACE) for treatment efficacy with different definitions of compliance
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Need for Strategic Health and Intervention Concept Changes with Current Epidemiologic Trends in Alcoholic Population
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Hierarchical Longitudinal Models of Relationships in Social Networks
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Ohio Electronic Health Records Survey: Increasing Response Rates Surveying Medical Practices
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Thu, Oct 6 |
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Poster Session II & Continential Breakfast |
7:30 AM - 8:30 AM
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Financial health equity. Intervention for balance and financial stability of national health providing institutions, , health promoters and insurers.
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Reimbursement price reduction and pharmaceutical firm production behavior in Korea
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Bias In Variance Estimation Using Re-Sampling Of Longitudinal And Nested Administrative Health Data.
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The power to identify patient subgroup effects with meta-analyses of randomized controlled trials
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Analyzing State-Based Silver Alert Programs: The Case of North Carolina
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Two Sample Distribution-Free Inference Based on Partially Rank Ordered Set Sample
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A Hotel Model for Studying the Effect of State Policies on Nursing Home Hospitalizations
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Estimating prevalence of multiple chronic conditions based on health behaviors and its regional differences in the United State, Behavioral Risk Factor Surveillance System, 2009
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Effectiveness of adolescent substance abuse treatments: An application using multinomial propensity scores
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A Bayesian Hierarchical Model to Estimate State-Level Support for Health Care Reform from National Opinion Data
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Modeling the volume-outcome relationship using high-dimensional patient-level covariate data across many hospitals
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Proper Variance Computation for Estimates from MEPS Event Files
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Bayesian Semi-parametric Joint Modeling of Item Response Model
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Sensitivity analysis for modeling nonignorable missingness in randomized controlled trials
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Using propensity scores to assess the relationship between HIV status and acute myocardial infarction in the Veterans Aging Cohort Study
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Are Provider Communication Constructs the Same Across English and Spanish?
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A Novel Approach to Quantify Risk for SUD: Computerized Adaptive Testing
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Predictors for longitudinal trajectory of Bone Mineral Density in Pediatric Systemic Lupus Erythematosus Patients
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Quantile Regression Analysis of the Effect of Health Maintenance Organization Enrollment on Medical Expenditures
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Semiparametric Regression Inference for Age-Stage at Diagnosis Relationship in Cancer Studies
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Validity of Using Census-Based Area Level Socioeconomic Information As a Proxy for Individual Level Socioeconomic Confounders in Instrumental Variables Regression
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Conference Registration |
7:30 AM - 5:00 PM
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Welcome and Keynote Address |
8:30 AM - 10:00 AM
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Chair(s): Thomas E. Love, Case Western Reserve University; Dr. A. James O'Malley, Harvard Medical School |
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Break |
10:00 AM - 10:30 AM
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Session 11 Invited New Developments in the Analysis of Incomplete Longitudinal Data |
10:30 AM - 12:15 PM
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Organizer(s): Ofer Harel, University of Connecticut; Recai Murat Yucel, State University of New York at Albany |
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Chair(s): Recai Murat Yucel, State University of New York at Albany |
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10:35 AM |
Informative priors and sensitivity analysis for longitudinal clinical trials with dropout
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11:00 AM |
Relevant, accessible sensitivity analysis using multiple imputation
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11:25 AM |
Multiply-robust adjustment for dependent drop-out in longitudinal studies
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Discussant(s): Roderick J. Little, University of Michigan |
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Session 12 Invited Spatial Methods for Health Policy Research |
10:30 AM - 12:15 PM
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Organizer(s): Brian Neelon, Duke University |
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Chair(s): Brian Neelon, Duke University |
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10:35 AM |
Latent spatial grouping in Bayesian AFT modeling
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11:00 AM |
Identification in Bayesian disease mapping and spatial regression
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11:25 AM |
Spatial Path Models with Multiple Indicators and Causes: Population Psychiatric Outcomes in US Counties
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11:50 AM |
Bayesian spatial quantile regression for projecting effects of climate change on onzone concentration
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Session 13 Topic-Contributed Papers Propensity Scores, Optimal Matching and Related Approaches |
10:30 AM - 12:15 PM
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Organizer(s): Thomas E. Love, Case Western Reserve University |
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Chair(s): Thomas E. Love, Case Western Reserve University |
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10:35 AM |
Contrasting evidence within and between institutions that supply treatment in an observational study of alternative forms of anesthesia
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10:55 AM |
The Use of Propensity Scores to Estimate Sample Selection Error in Observational Data
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11:15 AM |
Going Beyond a Pre-Post Design: Propensity Score Matching in a Cost Savings Framework for Nurse Care Management Program Evaluation
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11:35 AM |
Using Propensity Score Analysis to Assess the Effectiveness of Social Marketing Campaigns in Healthcare: An Example from Medicare Open Enrollment
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11:55 AM |
Augmenting Propensity Score Matching with Outcome Information
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Session 14 Contributed Papers Survey Methods and Related Topics |
10:30 AM - 12:15 PM
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Chair(s): Marc N. Elliott, RAND Corporation |
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10:35 AM |
Cumulative Distribution Plots to Enhance Interpretation of Treatment Differences on the Self-Esteem And Relationship Questionnaire for Men with Erectile Dysfunction
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10:55 AM |
Combining Information from Multiple Complex Surveys
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11:15 AM |
Health Characteristics of Medicare traditional fee-for-service and Medicare Advantage enrollees: 1999-2004 NHANES linked to 2007 Medicare data
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11:35 AM |
A Semi-Parametric Approach to Account for Complex Designs in Multiple Imputation
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11:55 AM |
Outliers in Non-Parametric Estimation of Treatment Effects
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Lunch on Your Own |
12:15 PM - 1:30 PM
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Session 15 Invited Investigating Treatment Effect Heterogeneity in Mental Health Research |
1:30 PM - 3:15 PM
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Organizer(s): Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health |
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Chair(s): Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health |
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1:35 PM |
Heterogeneity of the impact of mental health parity
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1:55 PM |
Tree-structured analysis of differential treatment effects
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2:15 PM |
Comparative Effectiveness of Medication vs. CBT in Depressed Low-income Women
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2:35 PM |
Using Structural Nested Mean Models to Examine Time-varying Moderators of the Effect of Substance Use Treatment
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Discussant(s): Thomas R. Belin, UCLA |
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Session 16 Invited Analytic Challenges in Complex Longitudinal Data from VA-related Health Services Research |
1:30 PM - 3:15 PM
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Organizer(s): Maren K. Olsen, Durham Epidemiology Research & Information Center (ERIC) |
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Chair(s): Maren K. Olsen, Durham Epidemiology Research & Information Center (ERIC) |
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1:35 PM |
Longitudinal Analysis of Real-time Momentary Pain Data in a Cohort of Osteoarthritis Patients
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2:00 PM |
Mood Changes Associated with Smoking in Adolescents: An Application of a Mixed-Effects Location Scale Model for Longitudinal Ecological Momentary Assessment (EMA) Data
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2:25 PM |
Sample Size Determination for Longitudinal Binary Data
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2:50 PM |
Analyzing VA Data - Promises and Challenges
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Session 17 Topic Contributed Papers Database and Simulation-Based Methods for Decision-Making |
1:30 PM - 3:15 PM
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Organizer(s): Kelly H. Zou, Pfizer Inc |
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Chair(s): Joseph C. Cappelleri, Pfizer, Inc. |
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1:35 PM |
Model based drug development: A clinical pharmacologist’s approach to quantitative decision-making
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1:55 PM |
Indirect Treatment Comparisons Using Simulation
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2:15 PM |
Application of Classification Tree Modeling in the Development of Adult Vehicular Trauma Triage Decision Rules
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2:35 PM |
Identifying subjects with low adherence to trial visit schedules in the long-term clinical trial
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2:55 PM |
Detecting data fabrication in clinical trials from cluster analysis perspective
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Session 18 Contributed Papers Modeling Costs in Medicine and Health Care |
1:30 PM - 3:15 PM
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Organizer(s): Lei Liu, University of Virginia |
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Chair(s): Joseph W. Hogan, Brown University |
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1:35 PM |
Generalized Semiparametric Models with Unknown Variance Function, with Application to Medical Cost Data
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1:55 PM |
International evidence on medical spending
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2:15 PM |
Perverse Perceptions of the Impact of Pay for Performance on Healthcare Disparities
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2:35 PM |
Jointly Modeling Healthcare Costs
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2:55 PM |
Joint Modeling of Medical Expenditure and Survival in Complex Sample Surveys
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Break |
3:15 PM - 3:30 PM
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Session 19 Invited Innovations in Randomized Experiments & Quasi-Experimental Studies in Health Policy |
3:30 PM - 5:15 PM
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Organizer(s): Amelia M. Haviland, RAND Corporation |
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Chair(s): Amelia M. Haviland, RAND Corporation |
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3:35 PM |
Analysis of post-treatment outcomes in group therapy studies under open enrollment
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3:55 PM |
Does the association between exposure to smoking in movies and adolescents’ desire to smoke depend on how smoking is portrayed: A randomized lab study with matched movie clips
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4:15 PM |
Evaluating the comparative effectiveness of promising treatment programs for adolescents in face of differential follow-up
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4:35 PM |
Assessing effects of survey mode on healthcare survey responses through experimental manipulation of order
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4:55 PM |
A randomized experiment to increase response rates to a healthcare survey among individuals with a high predicted probability of preferring Spanish
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Session 20 Invited Bayesian Clinical Trials: Using Priors and Planning for Post-Regulatory Translation |
3:30 PM - 5:15 PM
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Organizer(s): C. Daniel Mullins, University of Maryland |
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Chair(s): Kelly H. Zou, Pfizer Inc |
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3:35 PM |
Bayesian Medical Device Clinical Studies in the Regulatory Setting
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4:00 PM |
Bayesian Meta-Analyses for Comparative Effectiveness and Coverage Decisionsand
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4:25 PM |
Improving the coherence of sequential imputation via calibration
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4:50 PM |
Commensurate Priors for Incorporating Historical Information in Clinical Trials using General and Generalized Linear Models
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Session 21 Topic Contributed Panel Panel Discussion: What Does it Mean to be a Meaningful User of Electronic Health Records? |
3:30 PM - 5:15 PM
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Organizer(s): Laura Lee Johnson, NIH |
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Chair(s): Laura Lee Johnson, NIH |
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3:35 PM |
Panel Discussion: What Does it Mean to be a Meaningful User of Electronic Health Records?
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Session 22 Contributed Papers Longitudinal and Survival Analysis |
3:30 PM - 5:15 PM
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Chair(s): Douglas Gunzler, Case Western Reserve University |
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3:35 PM |
Estimating Insurance Spell Dynamics Using Longitudinal Survey Data
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3:55 PM |
A Bayesian Semiparametric Model for Bivariate Sparse Longitudinal Data
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4:15 PM |
Joint Modeling of Longitudinal Patient Reported Outcomes and Survival Data with Application to an Oncology Clinical Trial
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4:35 PM |
Learning in hierarchical Bayesian models for longitudinal and survival outcomes
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4:55 PM |
The effect of pre-hospital ADL trajectory on post-hospital ADL trajectory and mortality
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Reception at House of Blues Cleveland |
6:15 PM - 8:15 PM
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Fri, Oct 7 |
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HPSS Executive Committee Breakfast Meeting (By Invitation Only) |
7:30 AM - 8:30 AM
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Conference Registration |
7:30 AM - 12:00 PM
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HPSS Awards and Plenary Speaker |
8:30 AM - 10:00 AM
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Chair(s): Thomas E. Love, Case Western Reserve University; Dr. A. James O'Malley, Harvard Medical School |
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Break |
10:00 AM - 10:15 AM
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Session 23 Invited Recent Developments in Modeling Random Effects in Health Outcomes Data |
10:15 AM - 12:00 PM
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Organizer(s): Yulei He, Harvard Medical School |
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Chair(s): Christopher Schmid, Tufts University Medical Center |
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10:20 AM |
What to shrink? Random Effects in Discrete Data Meta-Analysis
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10:45 AM |
Classifying hospitals on process performance measures using flexible random-effects models
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11:10 AM |
Center-adjusted inference for a nonparametric Bayesian random effect distribution
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Discussant(s): Donald Hedeker, University of Illinois at Chicago |
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Session 24 Invited Innovative Methods of Random Assignment |
10:15 AM - 12:00 PM
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Organizer(s): Ben B. Hansen, University of Michigan |
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Chair(s): Ben B. Hansen, University of Michigan |
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10:20 AM |
Integrating experimental-design principles into community-partnered participatory research on disseminating evidence-based depression care in underserved urban areas
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10:40 AM |
Matched randomization in RCTs where subjects trickle in one at a time or in small batches
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11:00 AM |
Alternatives to the Pocock-Simon method for trickle-in random assignment
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11:20 AM |
Propensity Score Matching in Randomized Clinical Trials
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Discussant(s): Thomas E. Love, Case Western Reserve University |
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Session 25 Topic Contributed Papers Applied Topics in Causal Inference |
10:15 AM - 12:00 PM
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Organizer(s): Dr. A. James O'Malley, Harvard Medical School |
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Chair(s): Laura A. Hatfield, Harvard Medical School |
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10:20 AM |
Accountability Research for Air Quality Regulations Using Principal Stratification
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10:40 AM |
Instrumental Variables Methodology for Estimation of Peer Effects
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11:00 AM |
Defining the Study Population for an Observational Study to Ensure Sufficient Overlap: a Tree Approach
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11:20 AM |
Assessing the Causal Effect of Treatment Dosages in the Presence of Self-Selection
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11:40 AM |
What is the right amount of utilization in Home Health Care?
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Session 26 Contributed Papers Effective Statistical Design |
10:15 AM - 12:00 PM
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Chair(s): Juned Siddique, Northwestern University |
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10:20 AM |
Health disparities between bachelors and associates degree holders with similar job quality.
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10:40 AM |
A comparison of estimators for the harms of repeat cancer screening for use in health policy decision making
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11:00 AM |
Predictive inference for identifying outliers in health care providers
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11:20 AM |
Capture-Recapture Techniques to Evaluate Completeness of Administrative Health Databases for Chronic Disease Research: Effects of Misclassification Error
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11:40 AM |
A new dependence parameter approach to improve the design of cluster randomized trials with binary outcomes
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Lunch on Your Own |
12:00 PM - 1:30 PM
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Workshop 11 The Medical Expenditure Panel Survey (MEPS): A National Data Resource to Inform Health Policy |
1:30 PM - 3:15 PM
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Organizer(s): Jeffrey Rhoades, Agency for Healthcare Research and Quality |
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The purpose of this Workshop is to facilitate the use of the Medical Expenditure Panel Survey Household Component (MEPS HC) public use data files by the health services research community. To meet this objective, participants are provided with a general overview of the MEPS, a description of available data files, information about on-line data tools, and some examples of the type of research projects the MEPS data can support. Major changes have taken place in the Nation's health care delivery system over the last decade. The most notable is the recent passage of the Affordable Care Act. Also consider the rapid expansion of managed care arrangements such as health maintenance organizations, preferred provider organizations, and other provider networks that seek to minimize increases in health care costs. The MEPS is a vital national data resource designed to continually provide health service researchers, policymakers, health care administrators, businesses, and others with timely, comprehensive information about health care use and costs in the United States. Newly released MEPS public use files provide analysts with opportunities to create unique analytic files for policy relevant analysis in the field of health services research, such as access to care and health disparities. In order to capture the unparalleled scope and detail of the MEPS HC, analysts need to understand the complexities of MEPS data files and data file linkages. This workshop will provide the knowledge necessary to formulate research plans utilizing the various MEPS HC files and linkage capabilities. |
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1:30 PM |
The Medical Expenditure Panel Survey (MEPS): A National Data Resource to Inform Health Policy
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Important Dates & Deadlines
- May 31, 2011
Registration Deadline for All Session Presenters - September 1, 2011
Poster Abstract Online Submission Closes - September 9, 2011
Hotel Reservations Close - September 15, 2011
Conference Registration Closes