Violations of Assumptions in School-Based Single-Case Data: Implications for the Selection and Interpretation of Effect Sizes.
A wide variety of effect sizes (ESs) has been used in the single-case design literature. Several researchers have "stress tested" these ESs by subjecting them to various degrees of problem data (e.g., autocorrelation, slope), resulting in the conditions by which different ESs can be considered valid. However, on the back end, few researchers have considered how prevalent and severe these problems are in extant data and as a result, how concerned applied researchers should be. The current study extracted and aggregated indicators of violations of normality and independence across four domains of educational study. Significant violations were found in total and across fields, including low levels of autocorrelation and moderate levels of absolute trend. These violations affect the selection and interpretation of ESs at the individual study level and for meta-analysis. Implications and recommendations are discussed.
Oklahoma State University, Stillwater, USA benjamin.solomon@okstate.edu.
Benjamin George
BG
Solomon
D001519:Behavior; D003627:Data Interpretation, Statistical; D006801:Humans; D015203:Reproducibility of Results; D012107:Research Design; D018401:Sample Size; D012574:Schools
assumptions; autocorrelation; effect sizes; meta-analysis; single subject; trend