Education > Continuing Education

Web-Based Lectures

Previously recorded webinars are available through the LearnSTAT OnDemand program.

Current Webinar Offerings:


May 14, 2015 Interpretation of Patient-Reported Outcomes
June 4, 2015 Using SAS and LaTeX to Create Documents with Reproducible Results
June 24, 2015 Propensity Score Methods for Estimating Causal Effects in Pharmaceutical Research




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Title: Interpretation of Patient-Reported Outcomes
Presenter: Joseph Cappelleri, Pfizer, Inc.
Date and Time: Thursday, May 14, 2015, 12:00 p.m. - 2:00 p.m. Eastern time
Sponsor: Biopharmaceutical Section and Health Policy Statistics Section

Registration Deadline: Tuesday, May 12, at 12:00 p.m. Eastern time

Description:
A patient-reported outcome is any report on the status of a patient's health condition that comes directly from the patient. Clear and meaningful interpretation of patient-reported outcome scores are fundamental to their use as they can be valuable in designing studies, evaluating interventions, educating consumers, and informing health policy makers involved with regulatory, reimbursement, and advisory agencies. Interpretation of patient-reported outcome scores, however, is often not well understood because of insufficient data or lack of experience or clinical understanding to draw from.

This presentation provides an update review on two broad approaches - anchor-based and distributed-based - aimed at enhancing the understanding and meaning of patient-reported outcome scores. Anchor-based approaches include percentages based on thresholds, criterion-group interpretation, content-based interpretation, and clinical important difference. Distributed-based approaches include effect size, probability of relative benefit, and responder analysis and cumulative proportions.

A third strategy called mediation analysis, which can elucidate a health condition measured by a patient-reported outcome in the context of an intervention's mechanism of action, is also highlighted and illustrated. Mediation analysis in the context of interpretation of patient-reported outcome scores is a relatively new development.

The logic and rationale of the three methods are expressed generally. While the three approaches themselves are not new, some applications of them taken from their examples published in the past several years are original and coalesced in this presentation.

Registration Fees:
Biopharmaceutical Section Members: $44
Health Policy Statistics Section Members: $44
ASA Members: $59
Nonmembers: $74

Each registration is allowed one web connection and one audio connection. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Register



Access Information
Registered persons will be sent an email the afternoon of Tuesday, May 12, with the access information to join the webinar and the link to download and print a copy of the presentation slides.




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Title: Using SAS and LaTeX to Create Documents with Reproducible Results
Presenter: Tim Arnold, SAS Institute, Inc.
Date and Time: Thursday, June 4, 2015, 11:00 a.m. - 12:30 p.m. Eastern time
Sponsor: Section for Statistical Programmers and Analysts

Registration Deadline: Tuesday, June 2, at 12:00 p.m. Eastern time

Description:
This webinar will describe the StatRep system for reproducible research. The StatRep system uses SAS and the LaTeX typesetting system to create documents with reproducible results. It consists of a LaTeX package, a suite of SAS macros and a user guide.

The LaTeX package provides two environments and two tags that work together to display your SAS code and results and to generate the SAS program that produces those results. The generated SAS program includes calls to the StatRep SAS macros that use the SAS Output Delivery System (ODS) document to capture the output as external files.

With the StatRep system, you can share your LaTeX document with colleagues and be sure that your results are reproducible.

Registration Fees:
Member of the Section for Statistical Programmers and Analysts: $40
ASA Member: $65
Nonmember: $85

Each registration is allowed one web connection and one audio connection. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Register



Access Information
Registered persons will be sent an email the afternoon of Tuesday, June 2, with the access information to join the webinar and the link to download and print a copy of the presentation slides.




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Title: Propensity Score Methods for Estimating Causal Effects in Pharmaceutical Research
Presenter: Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health
Date and Time: Wednesday, June 24, 2015, 12:00 p.m. - 2:00 p.m. Eastern time
Sponsor: Biopharmaceutical Section

Registration Deadline: Monday, June 22, at 12:00 p.m. Eastern time

Description:
Propensity scores are an increasingly common tool for estimating the effects of interventions in observational ("non-experimental") settings and for answering complex questions in randomized controlled trials. They can be of great use in pharmaceutical and health services research, for example helping assess broad population effects of drugs, devices, or biologics already on the market, especially investigating post-marketing safety outcomes, or for answering questions regarding the outcomes of long-term use using claims data. This webinar will discuss the importance of the careful design of observational studies, and the role of propensity scores in that design, with the main goal of providing practical guidance on the use of propensity scores to estimate causal effects. The webinar will briefly cover the primary ways of using propensity scores to adjust for confounders when estimating the effect of a particular "cause" or "intervention," including weighting, subclassification, and matching. Topics covered will include how to specify and estimate the propensity score model, selecting covariates to include in the model, diagnostics, and common challenges and solutions. Software for implementing analyses using propensity scores will also be briefly discussed. The webinar will also highlight recent advances in the propensity score literature, with a focus on topics particularly relevant for pharmaceutical contexts, including prognostic scores, covariate balancing propensity scores, methods for non-binary treatments (such as dosage levels of a drug or when comparing multiple drugs, devices, or biologics simultaneously), and approaches to be used when there are large numbers of covariates available (as in claims data).

Registration Fees:
Biopharmaceutical Section Members: $44
ASA Members: $59
Nonmembers: $74

Each registration is allowed one web connection and one audio connection. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Register



Access Information
Registered persons will be sent an email the afternoon of Monday, June 22, with the access information to join the webinar and the link to download and print a copy of the presentation slides.