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Exploring Small-N Designs: Reversal and Multiple Baseline Strategies in Research

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Small-N designs focus on a limited number of subjects, emphasizing internal validity while acknowledging external validity concerns. Reversal designs (ABA) measure dependent variables before treatment, during treatment, and after treatment removal, though they are unsuitable for treatments with lasting effects. Variations such as ABAB and ABBA exist. Alternatively, multiple baseline designs compare behaviors before and after treatment across different subjects or scenarios, ideal for treatments with permanent impacts. Descriptive statistics, rather than inferential statistics, are used to present data visually in these designs.

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Exploring Small-N Designs: Reversal and Multiple Baseline Strategies in Research

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  1. SMALL-N DESIGNS • Experiments conducted on only one or a few subjects • External validity is a problem • Internal validity is often very good - no individual differences • Available population may be small

  2. Reversal Designs • Measure before treatment, with treatment, and after treatment is removed or reversed (ABA Design) • The treatment is the independent variable • Measure the dependent variable at each stage of the design

  3. Reversal Designs • Not appropriate for treatments with permanent effects • Variations: • ABAB • ABBA

  4. Multiple Baseline Designs • Compare before and with treatment; use other behaviors, situations, or subjects as baselines • Useful when treatment has permanent effect

  5. Multiple Baseline: Behaviors Behavior 1 before / Behavior 1 after Behavior 2 before ………. / Behavior 2 after Behavior 3 before ……………… TIME

  6. Multiple Baseline: Situations Situation 1 before / Situation 1 after Situation 2 before ………. / Situation 2 after Situation 3 before ……………… TIME

  7. Multiple Baseline: Subjects Subject 1 before / Subject 1 after Subject 2 before ………. / Subject 2 after Subject 3 before ……………… TIME

  8. Statistics for Small-N Designs • Inferential statistics are not used • Use descriptive statistics; show data graphically

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