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Square Lattice Designs in Incomplete Split-Plot Designs
Journal of Statistical Theory and Practice, 2007We construct an incomplete split-plot design by the semi-Kronecker product of two resolvable designs. We use any resolvable design for the treatments of whole-plots and a square lattice design for the treatments of subplots. We give the stratum efficiency factors for such incomplete split-plot designs, which have the general balance property.
Shinji Kuriki, Kiyoaki Nakajima
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Split-Plot Design: A Robust Analysis
1996This paper is devoted to the examination of the robustness of standard split-plot analysis for a two factors design with complete blocks under normality assumptions. For instance, in ceramics firing, the main factors are the oven temperature A and the clay mixture B.
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Split-plot designs: discussion and examples
International Journal of Quality Engineering and Technology, 2010Split-plot designs and the appropriate statistical analysis of the resulting data are frequently misunderstood by industrial experimenters. The objective of this tutorial paper is to review split-plot designs for full and fractional factorial experiments, explain why they often arise in industrial experiments, and provide several illustrative examples.
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Euphytica, 2010
The paper shows how the α-design (also known as generalised lattice) may be used for constructing incomplete split-plot designs and describes four different methods (A, B, C and D) of construction. Intra-block efficiency factors and theoretical considerations are used to compare the methods.
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The paper shows how the α-design (also known as generalised lattice) may be used for constructing incomplete split-plot designs and describes four different methods (A, B, C and D) of construction. Intra-block efficiency factors and theoretical considerations are used to compare the methods.
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Split-Plot Designs with Correlated Proportions
Psychological Reports, 1988An extension of McNemar's test for correlated proportions was presented in which subjects falling into McNemar's A and D categories are nested under two or more levels of one or more between-subjects factors. The main effect for the within-subjects factor is tested with the McNemar chi-squared statistic used for correlated proportions after collapsing
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Relative Efficiency of The Split-Plot Design
Experimental Agriculture, 1978SUMMARYFormulae are given to calculate the efficiency of the split-plot design, in which whole-plot treatments are arranged in randomized complete blocks. Efficiency for each of the whole-plot and split-plot treatment comparisons is discussed relative to three simpler designs.
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, 2010 A Study of Two Types of Split-Plot Designs
Journal of Quality Technology, 2016This paper discusses two types of split-plot designs, split-plot designs with few whole-plot factors and blocked split-plot designs. We provide a list of efficient designs and compare them with the designs available in the literature with respect to a s..
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