TY - JOUR
T1 - Power of a randomization test in a single case multiple baseline AB design
AU - Bouwmeester, Samantha
AU - Jongerling, Joran
N1 - Publisher Copyright:
Copyright: © 2020 Bouwmeester, Jongerling. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85079081072&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0228355
DO - 10.1371/journal.pone.0228355
M3 - Article
C2 - 32027683
AN - SCOPUS:85079081072
VL - 15
JO - PLOS ONE
JF - PLOS ONE
SN - 1932-6203
IS - 2
M1 - e0228355
ER -