Brief experimental analysis (BEA) is a well-documented analysis strategy that rapidly manipulates instructional variables to identify the most effective intervention to support a student’s academic needs. However, consensus on how BEA data should be evaluated is not evident in published BEA articles. This study investigated the agreement between evaluation methods (i.e., visual analysis, no assumptions effect size, percentage of nonoverlapping data, nonoverlap of all pairs) used in BEA. Overall, the measures of effect size resulted in a higher percentage of positive agreement with other measures of effect size, in comparison to visual analysis paired with effect size measures. Use of effect size measures also resulted in less equivalency between intervention outcomes within a BEA. These data suggest that using a measure of effect size can be a beneficial component to visual analysis; however, each measure of effect size has its own strengths and limitations and should be used cautiously when interpreting results of a BEA.
| Identifer | oai:union.ndltd.org:WKU/oai:digitalcommons.wku.edu:theses-3039 |
| Date | 01 July 2017 |
| Creators | Scharklet, Jennifer D |
| Publisher | TopSCHOLAR® |
| Source Sets | Western Kentucky University Theses |
| Detected Language | English |
| Type | text |
| Source | Masters Theses & Specialist Projects |
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