Values and Celeration Multipliers to Measure

Many scientific discoveries, such as the foundational concept of reinforcement (Skinner & Ferster, 1957) and elements of effective instruction (Christensen, Ysseldyke, & Thurlow, 1989), have stemmed from single case design (SCD) research. SCDs facilitate detection of a functional relationship between the introduction of an independent variable and changes in a dependent variable (Johnston & Pennypacker, 2009; Sidman, 1960). Using only a single or small number of participants, various SCDs (i.e., multiple-baseline and alternating treatment) can inform and hasten the development of scientific theory generalizable to larger populations (Horner et al., 2005). The power of SCD research lies in detection and replication of experimental effects. Replications occur when introduction or removal of an independent variable repeatedly results in a change in the dependent variable (Kazdin, 2011). For example, if Participant A improved following intervention, then a replication occurs when Participant B shows comparable experimental effects. The more replications demonstrated, the more confidence engendered by the intervention for its application to a wide range of people. SCD experimenters typically detect experimental effects and subsequent replication through the visual inspection of graphic displays for changes in level, trend, and variability within and between experimental phases (Kennedy, 2005). Level refers to the mean of data within the phase. Trend indicates the slope of data as increasing, decreasing, or remaining flat. The trend also has a magnitude usually expressed in qualitative terms: high, medium, and low (Kennedy). Variability occurs when data points vary from one another along a trend. Variability also finds its expression in qualitative terms with high, medium, and low. To report experimental results in SCDs, the scientific literature has a rich tradition of relyin