One approach for combining single-case data involves use of multilevel modeling. In this article, the authors use a Monte Carlo simulation study to inform applied researchers under which realistic conditions the three-level model is appropriate. The authors vary the value of the immediate treatment effect and the treatment's effect on the time…

Hawkin's procedure for testing a sequence of observations for a shift in location could have applicability for assessing change within a single subject. Monte Carlo results suggest that Hawkins' procedure is robust with respect to moderate violations of its underlying assumptions of homogeneity of variance and normality. (Author/GDC)

Monte Carlo methods were used to estimate the power of randomization tests used with single-case designs involving random assignment of treatments to phases. Simulations of two treatments and six phases showed an adequate level of power when effect sizes were large, phase lengths exceeded five, and autocorrelation was not negative. (SLD)