Nonlinear Bayesian analysis for single case designs

• Published in: Journal of school psychology Vol. 52; no. 2; pp. 179 - 189
• Main Author: Rindskopf, David
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.04.2014
• Subjects: Bayes Theorem; Bayesian; Bayesian analysis; Computers; Data Interpretation, Statistical; Humans; Multilevel; Nonlinear; Nonlinear Dynamics; Parameters; Random effects; Research Design - standards; Single case; Single subject; Uncertainty; Single case; Nonlinear; Multilevel; Single subject; Bayesian
• ISSN: 0022-4405; 1873-3506; 1873-3506
• DOI: 10.1016/j.jsp.2013.12.003

Several authors have suggested the use of multilevel models for the analysis of data from single case designs. Multilevel models are a logical approach to analyzing such data, and deal well with the possible different time points and treatment phases for different subjects. However, they are limited in several ways that are addressed by Bayesian methods. For small samples Bayesian methods fully take into account uncertainty in random effects when estimating fixed effects; the computational methods now in use can fit complex models that represent accurately the behavior being modeled; groups of parameters can be more accurately estimated with shrinkage methods; prior information can be included; and interpretation is more straightforward. The computer programs for Bayesian analysis allow many (nonstandard) nonlinear models to be fit; an example using floor and ceiling effects is discussed here.