• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.245-251
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• 2008

The research proposes three ANOVA(Analysis of Variance) tests using expected mean square(EMS) algorithms in various split-plot designs. The variance tests consist of Never-Pool test, Sometimes-Pool test and Always-Pool test. This paper also presents two EMS algorithms such as standard method and easy method. These algorithms are useful to make a decision rule for pooling. Numerical examples are illustrated for various split-plot designs such as split-plot designs, split-split-plot designs, repetition split-plot designs, and nested designs. Pragmatically, the results are summarized and compared with popular ANOVA spreadsheets and data model equations.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.277-292
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• 2012

The research presents an application of Balanced ANOVA (BANOVA) by utilizing randomized orders for various Split-Plot Designs (SPDs) which include two cell designs, split-plot with one-way HTC (Hard to Control) factor, split-plot with two-way HTC factor, split-split-plot design and nested design. In addition, four MINITAB examples of 2-level split-plot designs based on the number of blocks and the type of whole-plots are presented for practitioners to obtain comprehensive understanding. Furthermore, the geometrical interrelated properties among three typical Designs of Experiments (DOE), such as Factorial Design (FD), Response Surface Design (RSD), and Mixture Design (MD) are discussed in this paper.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.649-657
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• 2009

The paper presents the measurement split split-plot models for saving the time and cost. The split split-plot designs developed are efficiently used to estimating the gauge R&R(Reproducibility & Repeatability) when the completely randomized design of all factors(such as high pressure and temperature) is expensive and time consuming. The models studied include three split split-plots considering the type of experimental units.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.487-493
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• 2011

The paper reviews three Split Plot Designs (SPDs) of fixed factors, and those are SPD (RCBD, RCBD), SPD (CRD, RCBD) and SBD (Split Block Design). RCBD (Randomized Complete Block Design) and CRD (Completely Randomized Design) are used to deploy whole plot and sub plot. The models explained in this study are derived from random, crossed and nested models.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.335-344
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• 2017

This paper discusses a method of analyzing data from split-plot experiments by projections. The assumed model for data has two experimental errors due to two different experimental sizes and some random components in treatment effects. Residual random models are constructed to obtain sums of squares due to random effects. Expectations of sums of squares are obtained by Hartley's synthesis. Estimable functions of fixed effects are discussed.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.481-486
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• 2011

The research reviews three experimental designs which include Split Plot Design (SPD), Crossover Design (CD) and Replicated Design (RD) by using Latin Square Design (LSD). SPD (CRD, LSD) and SPD (LSD, RCBD) that are derived from (S:A)${\times}B{\times}C{\times}D$ and $A{\times}B{\times}C{\times}D$. In addition, (S:A)${\times}B{\times}C$, (S:A)${\times}C{\times}D$ and (S:A)${\times}B{\times}C{\times}D$ can be used to generate various LSD and CD models. Finally, Replicated LSDs are considered to increase the power of detectability.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.139-149
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• 1997

For split plot designs exact univariate F tests of the within-subjects main effect are based on the assumption of multisample sphericity. Type I error rates and power are reported for the F test and two tests designed for use when multisample sphericity is violated: the $\widetilde{\xi}$-adjusted test and the Corrected Improved General Approximation(CIGA) test.The results indicate that even though the F test and the $\widetilde{\xi}$-adjusted test have better power than the CIGA test in some conditions, the F test and the $\widetilde{\xi}$-adjusted test do not control Type I error rates when the design is unbalanced and the F test dose not have a good control of Type I error rates when sphericity assumption is severely violated.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.291-299
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• 2008

This paper discusses model building for repeated binary response data with different time-dependent covariates each occasion. Since repeated measurements data are having correlated structure, weighed least squares(WLS) methodology is applied. Repeated measures designs are usually having different sizes of experimental units like split-plot designs. However repeated measures designs differ from split-plot designs in that the levels of one or more factors cannot be randomly assigned to one or more of the sizes of experimental units in the experiment. In this case, the levels of time cannot be assigned at random to the time intervals. Because of this nonrandom assignment, the errors corresponding to the respective experimental units may have a covariance matrix. So, the estimates of effects included in a suggested logit model are obtained by using covariance structures.

• Journal of Korean Society for Quality Management
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• v.33 no.3
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• pp.156-160
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• 2005

We consider practical experimental design strategies and analysis to find out whether a modified method give better results than the standard method. The most practical design strategy is for experimenter to make r successive runs under the current standard method and then, change the standard method to a modified method to make another r successive runs under a modified method. To test a statistically significant difference between the population mean of the standard method and a modified method, additional recent data for sufficient number of consecutive responses under the standard method is needed to construct external reference distribution(Box, et al., 1968). Upon those informations unavailable, the practical design strategy is to run the experiment by split plot designs. In this paper, two types of split plot designs are proposed and how to determine efficiently the number of repetition within a given method and replication of those two methods are discussed based on results of the level of significance ${\alpha}$= 0.05 and the power being at least 0.9 at the detectable difference of ${\mu}_2-{\mu}_1=1.5{\times}{\sigma}$.