We conducted a Monte-Carlo study to investigate the influence of single-case research design chracteristics (phase length, initial DV level, intervention effect, trend) on the test power of piecewise Poisson-regression models. PLM have a high potential of adequately identifying intervention effects in single-case research designs. However, few measurement times, especially in phase A, and low initial DV levels make it impossible to detect even large intervention effects. Research designs with a high number of measurement times show robust power.
We had 186 pre-service teachers visually analyze single-case graphs, representing an intervention effect, a baseline trend, both, or no change at all. The presence of a baseline trend increased type I errors from 5% to 25%. Inter- and intra-rater reliabilities were low, particularly for graphs including a baseline trend.
Interventions to support children with mathematical learning difficulties typically address deficits in domain-specific knowledge. However, not all students benefit from these instructional programs. In this case, some authors suggest an even more …