Psychological Methods. 22(4):743–759, DEC 2017
DOI: 10.1037/met0000134
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PMID: 28406673
Issn Print: 1082-989X
Publication Date: 2017/12/01
Bayesian Unknown Change-Point Models to Investigate Immediacy in Single Case Designs
Prathiba Natesan;Larry Hedges;
+ Author Information
Department of Educational Psychology, University of North TexasDepartment of Statistics, Northwestern University
Abstract
Although immediacy is one of the necessary criteria to show strong evidence of a causal relation in single case designs (SCDs), no inferential statistical tool is currently used to demonstrate it. We propose a Bayesian unknown change-point model to investigate and quantify immediacy in SCD analysis. Unlike visual analysis that considers only 3–5 observations in consecutive phases to investigate immediacy, this model considers all data points. Immediacy is indicated when the posterior distribution of the unknown change-point is narrow around the true value of the change-point. This model can accommodate delayed effects. Monte Carlo simulation for a 2-phase design shows that the posterior standard deviations of the change-points decrease with increase in standardized mean difference between phases and decrease in test length. This method is illustrated with real data.
