Determining the significance of scale values from multidimensional scaling profile analysis using a resampling method.
Although multidimensional scaling (MDS) profile analysis is widely used to study individual differences, there is no objective way to evaluate the statistical significance of the estimated scale values. In the present study, a resampling technique (bootstrapping) was used to construct confidence limits for scale values estimated from MDS profile analysis. These bootstrap confidence limits were used, in turn, to evaluate the significance of marker variables of the profiles. The results from analyses of both simulation data and real data suggest that the bootstrap method may be valid and may be used to evaluate hypotheses about the statistical significance of marker variables of MDS profiles.
Ding
Cody S
CS
College of Education, University of Missouri, St. Louis, MO 43121, USA. dinghc@umsl.edu
D002321:Career Choice; D003198:Computer Simulation / Q000706:statistics & numerical data; D016001:Confidence Intervals; D006801:Humans; D007206:Individuality; D015233:Models, Statistical; D011581:Psychological Tests / Q000706:statistics & numerical data; D011589:Psychology, Experimental / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012494:Sampling Studies