Annual Meeting Recordings are now available for purchase
Propensity Score Matching Using R for Public Health Research -- Fee: $275
Saturday, November 15, 2014: 9:00 AM - 12:30 PM
Partnership: APHA Section on Applied Public Health Statistics.
Statement of Purpose and Institute Overview:
The purpose of this course is to introduce basic concepts of propensity score matching (PSM) and the use of R packages for PSM. Researchers in many fields including public health often use observational data to evaluate program effects because randomized controlled trials or experimental designs are not always feasible. The use of observational data threatens the validity of causal inference in program evaluation by introducing selection bias into the treatment assignment. To tackle this problem, PSM was developed to balance the distributions of observed covariates between treatment conditions as a means of reducing selection bias. PSM has been gaining popularity in causal inference and is actively applied in medical and other research areas, but much less so in public health research. To meet the educational need, promoting the use of PSM is imperative and beneficial to the improvement of the quality of program evaluation in public health research. This course is relevant to current public health concerns because through mini-lectures and hands-on activities, participants in this course will learn why and when we need PSM in public health research and how to perform PSM using R packages on public health data. This course is appropriate for faculty members, graduate students, and applied researchers in the public health community. To address the needs described above, we will focus on the applications of PSM while introduce the basic concepts to the participants. The course is designed to be practical. Prior to the in-class lectures and activities, instructions for downloading and installing R software and related packages as well as example datasets will be provided to participants in advance through a course website. No prior knowledge of R or PSM is required, but a basic understanding of t-tests and logistic regression is desirable. Participants are required to bring their own laptop computers for hands-on activities. This workshop is recommended for beginning level participants.
Session Objectives: Describe the basic concepts and main features of PSM.
Explain why and when to apply PSM in public health research.
Demonstrate the use of R packages for PSM on public health data and describe PSM results.
See individual abstracts for presenting author's disclosure statement and author's information.
Organized by: APHA-Learning Institute (APHA-LI)
Medical (CME), Health Education (CHES), Nursing (CNE), Public Health (CPH)
Masters Certified Health Education Specialist (MCHES)