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Modeling Strategies for Analyzing Complex Patient-Reported Outcomes (Virtual)

LEVEL: Intermediate
TRACK: Patient Centered Research
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

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Tuesday, 24 May 2022 | Course runs 2 consecutive days, 2 hours per day
10:00AM–12:00PM Eastern Daylight Time (EDT)
14:00PM–16:00PM Coordinated Universal Time (UTC)
16:00PM–18:00PM Central European Time (CET)

Wednesday, 25 May 2022 | Course runs 2 consecutive days, 2 hours per day
10:00AM–12:00PM Eastern Daylight Time (EDT)
14:00PM–16:00PM Coordinated Universal Time (UTC)
16:00PM–18:00PM Central European Time (CET)

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DESCRIPTION

Patient-reported outcomes (PROs) are usually measured under various complex research scenarios, such as cross-sectional vs. longitudinal design, unidimensional vs. multidimensional PROs, and homogeneous vs. heterogeneous population. The complexity poses methodological challenges for researchers to select appropriate models to analyze complex PROs. In this short course, faculty will discuss various modeling strategies for analyzing complex PROs with illustrations on real-world data. We will also introduce relevant R and SAS programs for analyzing complex PROs. This course will be beneficial for researchers to analyze complex PROs appropriately. A working knowledge of data analysis using statistical linear models is required. Participants are also required to bring their personal laptops equipped with sample data and program code which will be provided to course registrants.

FACULTY MEMBERS

Wei Pan, PhD
Associate Professor
Duke University
Durham, NC, USA

Xianming Tan, PhD
Research Associate Professor 
University of North Carolina at Chapel Hill
Chapel Hill, NC, USA

Basic Schedule:
Class Time: 2 hours daily