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The machine-learning classifier ALLCatchR2 identifies 20 T-ALL subtypes across cohorts and age groups. [PDF]
HemasphereBeder T +17 more
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Optimal split‐plot orthogonal arrays
Australian & New Zealand Journal of Statistics, 2017 SummaryIt is well known that many industrial experiments have split‐plot structures. Compared to completely randomised experiments, split‐plot designs are more economical and thus have received much attention among researchers. Much work has been done for two‐level split‐plot designs.
Yang, Po, Lin, Chang-Yun
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Journal of Quality Technology, 1973
The nature and uses of the split-plot design are discussed. An initial section reviews models and least squares to establish a point of view. The major section presents the development of a simple split-plot design by a process of "evolution,"..
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The nature and uses of the split-plot design are discussed. An initial section reviews models and least squares to establish a point of view. The major section presents the development of a simple split-plot design by a process of "evolution,"..
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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.
Johannes Ledolter
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Quality and Reliability Engineering International, 2007
AbstractIn many experimental situations, practitioners are confronted with costly, time consuming, or hard‐to‐change (HTC) factors. These practical or economic restrictions on randomization can be accommodated with a split‐plot design structure that minimizes the manipulation of the HTC factors.
Peter A. Parker +3 more
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AbstractIn many experimental situations, practitioners are confronted with costly, time consuming, or hard‐to‐change (HTC) factors. These practical or economic restrictions on randomization can be accommodated with a split‐plot design structure that minimizes the manipulation of the HTC factors.
Peter A. Parker +3 more
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Split-Plot and Split-Block Designs
2020Split-plot and Split-block designs belong to a class of designs in which the inter-block information is utilized fully. These designs arose from agricultural experiments where there is a necessity to consider plots of different sizes, as plots of comparable sizes may not be available.
N. R. Mohan Madhyastha +2 more
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Fraction of Design Space Plots for Split‐plot Designs
Quality and Reliability Engineering International, 2006AbstractIn industrial experiments, restrictions on the execution of the experimental runs or the existence of one or more hard‐to‐change factors often leads to split‐plot experiments, where there are two types of experimental units and two independent randomizations.
Li Liang 0002 +2 more
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On the Analysis of Split-Plot Experiments
Biometrics, 1961A crucial question in the analysis of split-plot experiments is whether or not the interaction between subplot treatments and replications should be pooled with the three-factor interaction of main-plot treatments, subplot treatments, and replications, the result being called subplot error.
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A Split-Plot Experiment with Factor-Dependent Whole-Plot Sizes [PDF]
Journal of Quality Technology, 2011 Problem: The dairy company FrieslandCampina had an opportunity to redesign the production process for its coffee cream. This product has a very specific viscosity, and the redesigned process had to result in the same viscosity as the old one. Approach: For an effective redesign, the investigators wanted to obtain a simple model linking the settings of ...
SCHOEN, Eric D. +2 more
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Biometrics, 1967
A split plot design for the factorial treatment combinations of factors A and B with t and s levels respectively, consists of wholeplots made up of s subplots or experimental units with each level of A applied to r wholeplots and the levels of B applied to the s subplots within each wholeplot.
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A split plot design for the factorial treatment combinations of factors A and B with t and s levels respectively, consists of wholeplots made up of s subplots or experimental units with each level of A applied to r wholeplots and the levels of B applied to the s subplots within each wholeplot.
openaire +2 more sources