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The continuation of a baseline pattern of responding into a treatment phase, sometimes referred to as a "transition state," can obscure interpretation of data depicted in single-case experimental designs (SCEDs). For example, when using visual analysis, transition states may lead to the conclusion that the treatment is ineffective. Likewise, the inclusion of overlapping data points in some statistical analyses may lead to conclusions that the treatment had a small effect size and give rise to publication bias. This study reviewed 20 volumes in a journal that publishes primarily SCEDs studies. We defined a transition state as a situation wherein at least the first three consecutive data points of a treatment phase or condition are within the range of the baseline phase or condition. Results indicate that transitions states (a) were present for 7.4% of graphs that met inclusion criteria and (b) occurred for a mean of 4.9 data points before leading to behavior change. We discuss some implications and directions for future research on transition states.
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| http://dx.doi.org/10.1177/0145445519839213 | DOI Listing |
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