Interval estimation for linear functions of medians in within-subjects and mixed designs |
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Authors: | Douglas G. Bonett Robert M. Price |
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Affiliation: | 1. Department of Psychology, University of California, Santa Cruz, California, USA;2. Department of Mathematics and Statistics, East Tennessee State University, Johnson City, Tennessee, USA |
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Abstract: | The currently available distribution-free confidence interval for a difference of medians in a within-subjects design requires an unrealistic assumption of identical distribution shapes. A confidence interval for a general linear function of medians is proposed for within-subjects designs that do not assume identical distribution shapes. The proposed method can be combined with a method for linear functions of independent medians to provide a confidence interval for a linear function of medians in mixed designs. Simulation results show that the proposed methods have good small-sample properties under a wide range of conditions. The proposed methods are illustrated with examples, and R functions that implement the new methods are provided. |
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Keywords: | confidence intervals distribution-free longitudinal design paired-sample design pretest–posttest design robust |
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