Applying Bayesian Statistics for Estimating Intervention Effects in Single-Case Designs

• In Event: 52.034 - Single-Case Designs and Small Sample Issues

Abstract

Single-case design is a repeated-measures research approach for the study of the effect of an intervention, and its importance is increasingly being recognized in education and psychology. We propose a Bayesian approach for estimating intervention effects in SCD. A Bayesian inference does not rely on large sample theories and thus is particularly suitable for SCD studies. The aims of this paper are to (1) introduce a Bayesian analysis approach for SCD studies, (2) provide a freely available and user-friendly R function, and (3) demonstrate the use of the R function in an empirical data set. We anticipate that this paper will lead to an increase in the number of SCD researchers applying and benefiting from a Bayesian approach.

Authors

• Li-Ting Chen, University of Nevada, Reno

• Alejandro Andrade, Indiana University - Bloomington

• Matthew James Hanauer, Indiana University - Bloomington