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Steve P. Verrill

USDA Forest Products Laboratory



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David E. Kretschmann

USDA Forest Products Laboratory



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255 – Experimental Designs I

Problems with a Type of Matched Subjects Design and Analysis

Sponsor: Section on Physical and Engineering Sciences
Keywords: predictor sort, matched subjects, blocking by a concomitant variable, analysis of variance, analysis of covariance, artificial pairing

Steve P. Verrill

USDA Forest Products Laboratory

David E. Kretschmann

USDA Forest Products Laboratory

There is a type of blocked experiment that has the potential of being poorly designed and/or analyzed. Verrill et al (1993, 1999, 2004) referred to such an experiment as a "predictor sort" experiment. David and Gunnink (1997) spoke of "artificial pairing." In text books, it is sometimes referred to as a "matched pair" or "matched subjects" design. The associated design process is also sometimes described as "forming blocks via a concomitant variable." Improperly designed and/or analyzed, predictor sort experiments can be associated with incorrect/inadequate power calculations and sample sizes, incorrect tests of hypotheses, and incorrect confidence intervals. In this paper, we review some of the results in the literature, add a section on multiple comparisons, and present results from power and confidence interval coverage simulations that emphasize the importance of proper design and analysis of predictor sort experiments.

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