A Randomization Test SAS/IML® Program for Making Treatment Effects Inferences for Extensions and Variations of ABAB Single-Case Experimental Designs

While the evaluation of intervention effects in single-case research has relied on visual inspection of the data (Kazdin, 1980), the description of graphical forms are not considered an adequate substitute for statistical tests (Edgington, 1980). Moreover, there are cases when graphical displays of data tend to be quite ambiguous and treatment effects are not easily appreciated (Ferron & Sentovich, 2002); in these cases, inferential statistics are often necessary to determine if a treatment effect exists. Randomization tests are considered valid statistical tests for determining the presence of a treatment effect in single-case experimental data (Edgington, 1980). In addition, significance tests lead to a more informed and reflective statistical analysis (Thompson & Snyder, 1997). Although the statistical validity of randomization tests has been established, randomization tests for single-case data are not incorporated into readily available statistical software like SAS® and SPSS, making it difficult for researchers to implement randomization tests into their statistical analysis of data. The example provided for Onghena (1992) was used to illustrate a worked example of a randomization test where the use of random assignment of treatment to treatment times and the incorporation of randomization into single-case reversal designs is explained and applied to statistical testing. SAS/IML code for randomization tests for extensions and variations of ABAB single-case experimental designs is provided and discussed.