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Define the percentage of non-overlapping data (PND) as it is used in single-subject research, and provide a concise analytical description of the specific steps required to calculate this statistical metric based on baseline and treatment responses.
Question: Define the percentage of non-overlapping data (PND) as it is used in single-subject research, and provide a concise analytical description of the specific steps required to calculate this statistical metric based on baseline and treatment responses.
Sample answer: The percentage of non-overlapping data (PND) is a statistical metric used to summarize the effectiveness of an intervention in single-subject research. It is calculated by first identifying the single most extreme response recorded in the control or baseline condition. Once that value is identified, the researcher calculates the percentage of responses in the treatment condition that are more extreme than that specific baseline measurement.
Key points:
- Identify PND as a statistical metric used to summarize intervention effectiveness.
- Note that it is specifically used in single-subject research.
- State the requirement to identify the single most extreme response in the baseline or control condition.
- Explain that the final metric is the percentage of treatment responses that are more extreme than the single highest baseline response.
Rubric: A full-credit response must accurately define PND as a metric for evaluating intervention effectiveness in single-subject research and correctly detail its calculation by comparing the frequency of extreme treatment responses to the single most extreme baseline response.
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Research Methods in Psychology - 4th American Edition @ KPU
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Example of Percentage of Non-Overlapping Data: Robbie's Study Time
In single-subject research, how is the percentage of non-overlapping data (PND) calculated?
Arrange the steps in the correct order to calculate the percentage of non-overlapping data (PND) in a single-subject research design.
In single-subject research, the Percentage of Non-Overlapping Data (PND) provides a summary of intervention effectiveness. Match each hypothetical data pattern to the specific analytical consequence it has on the PND calculation and its interpretation.
A researcher's evaluation of a treatment as 'ineffective' based solely on a Percentage of Non-Overlapping Data (PND) of may be logically flawed if the intervention produced a consistent improvement that simply failed to exceed one unusually extreme baseline measurement.
You are 'creating' a hypothetical dataset for a research methods tutorial to illustrate a 'moderately strong' intervention effect. Your goal is to produce a data sequence with a Percentage of Non-Overlapping Data (PND) of exactly . Given a baseline dataset of for an intervention aimed at increasing a behavior, which of the following sets of four treatment observations would you 'synthesize' to satisfy this design requirement?
The percentage of non-overlapping data (PND) is calculated by identifying the percentage of responses in a treatment condition that are more extreme than the average response in the baseline condition.
A researcher evaluates a behavioral intervention using a single-subject design to increase a student's on-task behavior. The baseline phase yields the following focus durations (in minutes): 4, 7, 5, and 8. The treatment phase yields: 10, 8, 12, 11, and 9 minutes. The Percentage of Non-Overlapping Data (PND) for this intervention is _____.
Match each hypothetical single-subject study scenario to the corresponding Percentage of Non-Overlapping Data (PND) value it yields.
A researcher is analyzing Robbie's study time data. The baseline phase yields measurements of 10, 14, 11, and 15 minutes. The subsequent treatment condition yields measurements of 18, 13, 17, 19, and 16 minutes. To analyze the effectiveness of the intervention, the researcher calculates the Percentage of Non-Overlapping Data (PND) to be _____ percent.
Arrange the steps in the correct order to evaluate the effectiveness of a single-subject behavioral intervention using the Percentage of Non-Overlapping Data (PND) metric.
Define the percentage of non-overlapping data (PND) as it is used in single-subject research, and provide a concise analytical description of the specific steps required to calculate this statistical metric based on baseline and treatment responses.
Based on this calculated PND of , how should the researcher interpret the effectiveness of the intervention according to the standard principles of evaluating percentage of non-overlapping data?
A researcher is evaluating an intervention using a single-subject design. The baseline condition yields response scores of 4, 3, 5, and 2. The subsequent treatment condition yields response scores of 6, 4, 7, 8, and 6. If higher scores represent the intended 'extreme' direction, apply the standard procedure to calculate the percentage of non-overlapping data (PND) for this intervention. Briefly state your final percentage and the specific numbers you used to determine it.