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ERIC Number: ED606869
Record Type: Non-Journal
Publication Date: 2017-Apr-30
Pages: 15
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-
EISSN: N/A
Available Date: N/A
Applying Bayesian Statistics for Estimating Intervention Effects in Single-Case Designs
Chen, Li-Ting; Andrade, Alejandro; Hanauer, Matthew James
AERA Online Paper Repository, Paper presented at the Annual Meeting of the American Educational Research Association (San Antonio, TX, Apr 27-May 1, 2017)
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.
AERA Online Paper Repository. Available from: American Educational Research Association. 1430 K Street NW Suite 1200, Washington, DC 20005. Tel: 202-238-3200; Fax: 202-238-3250; e-mail: subscriptions@aera.net; Web site: http://www.aera.net
Publication Type: Speeches/Meeting Papers; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A