Power of a randomization test in a single case multiple baseline AB design

• Published in: PloS one Vol. 15; no. 2; p. e0228355
• Main Authors: Bouwmeester, Samantha, Jongerling, Joran
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 06.02.2020; Public Library of Science (PLoS)
• Subjects: Analysis; Biometry; Computer Simulation; Cross-Over Studies; Design; Engineering and Technology; Humans; Inspection; Intervention; Methods; Normal distribution; Observation; Physical Examination; Physical Sciences; Power (Philosophy); Psychological research; Random Allocation; Randomization; Research and Analysis Methods; Research design; Research Design - standards; Research Design - statistics & numerical data; Researchers; Sample Size; Single subject research; Single-Case Studies as Topic - methods; Single-Case Studies as Topic - statistics & numerical data; Statistical analysis; Studies; Time series; Validity; Netherlands
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0228355

A randomization test can be used to statistically test hypotheses in multiple baseline designs to complement the commonly used visual inspection analysis. A crossed factor simulation study was performed to investigate the power of a randomization test in an multiple baseline design. The results show that the degree of autocorrelation of the observations, the number of participants, the effect size, the overlap of possible start moments of the intervention between participants, the ratio of the number of measurements in the baseline- and intervention phase, a gradually emerging effect, and the number of measurements had strong main effects on the power. The two-way interactions between number of participants and effect size, and between the number of measurements and the number of start moments of the intervention also had a large effect. An online tool was developed to calculate the power of a multiple baseline design given several design characteristics.