Webinar Series
A Demonstration of Two-Stage Analysis of Delay Discounting Data Using R
Chris Franck (Virginia Tech)
Abstract: The purpose of this webinar is to provide a tutorial in two-stage analysis of delay discounting data using the free R statistical programming package. In the first stage of analysis, participant-level discounting parameter estimates are obtained by fitting discounting models to indifference points. Once the parameter estimates (e.g., lnk estimates) are obtained, the second stage of analysis uses participant data (e.g. group membership or other subject characteristics) to model discounting rates as a function of predictors of interest. The two-stage approach to analysis strikes a nice balance since it is reasonably easy to execute and it also meets statistical assumptions of independence common to most off-the-shelf data analysis techniques. The virtues and caveats of the two-stage approach will be discussed further relative to other possible ways to analyze discounting data. Participants will be invited to participate in the tutorial by running available code alongside the instructor, with a special emphasis on demonstrating R for audience members who may not have used it previously. Immediately after the lecture portion, a totally optional, unscripted, one hour Q&A/discussion will take place, and which point we will discuss whatever statistical topics are of interest to the audience. This may include live coding demonstrations and discussions of other topics that pertain to the analysis of discounting data.
Instruction Level: Intermediate
Learning Objectives:
At the conclusion of the presentation, participants will be able to: (1) download, install, and run existing code in R; (2) explain delay discounting data analysis as it pertains to obtaining individual discounting rates from indifference points (first stage) and associating those rates with relevant predictor variables (second stage); (3) Implement basic analyses in part (2) with provided code and data example.
1 BACB CEU available.
Biography:
Chris Franck is an associate professor in the Department of Statistics at Virginia Tech.
CE Package
This item is available to current ABAI members only.
Learning Center Video and Quiz