Explain how comparing the baseline and post-intervention trends of both School A and School B allows the researchers to make a stronger claim about the effectiveness of the attendance reward system compared to if they only collected data from School A.
Case context: A school district wants to evaluate the impact of a new attendance reward system on student absences. Because they cannot randomly assign individual students or classrooms, they implement the reward system at School A (the treatment group) but not at School B (the control group). The district tracks the weekly absence rates at both schools for 10 weeks before the program starts and 10 weeks after it is introduced.
Question: Explain how comparing the baseline and post-intervention trends of both School A and School B allows the researchers to make a stronger claim about the effectiveness of the attendance reward system compared to if they only collected data from School A.
Sample answer: Comparing both schools allows researchers to rule out alternative explanations like history threats or seasonal changes (e.g., a flu outbreak or weather changes that naturally affect attendance). If we only track School A and absences drop, we cannot prove the reward system caused it rather than an external factor. By comparing School A's trends to the nonequivalent control, School B, if the drop in absences only occurs in School A while School B's trend remains unchanged, we obtain stronger evidence that the reward system was the cause.
Key points:
- Identifies that tracking only one group (School A) cannot rule out confounding variables or history threats over time.
- Explains that the nonequivalent control group (School B) serves as a comparison baseline for external temporal changes.
- Articulates that comparing the baseline and post-intervention trends across both groups helps attribute the change to the intervention.
Rubric: The student must show understanding that tracking a control group helps rule out external variables (like seasonal trends or history events). They must describe how comparing the baseline and post-intervention trends of the treatment group (School A) to the control group (School B) isolates the intervention's effect.
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Research Methods in Psychology - 4th American Edition @ KPU
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Example of an Interrupted Time-Series Design with Nonequivalent Groups: Student Absences
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