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Split-Plot Designs: A Useful Tool for the Statistical Analysis of Real Medical Data and Repeated Measurement Problems

C. Koukouvinos, E. Lygkoni, K. Mylona

Abstract


In this article, a split-plot design is applied for the collection of real medical data concerning biochemical and vital measurements of 283 patients in Intensive Care Unit, on a repeated measurement problem. Practical limitations and issues related to cost reveals frequently the practical usefulness of split-plot designs. When an experiment is planned, factors that are difficult or time consuming to manipulate appear and make complete randomization impractical. A split-plot structure is used when it is impractical to change the levels of some of the experimental factors. Our dataset, selected with the aid of a split-plot design, consists of 2256 observations 17 factors and 8 repetitions. A statistical analysis on the resulting data is performed and useful biological justification of our results is provided.

Keywords


repeated measures, restricted randomization, sequential processes, split-plot design, sub plot, variable selection, whole plot

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