• Journal of the Korean Statistical Society
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• v.26 no.1
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• pp.89-100
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• 1997

In this paper we are concerned with comparing ordered treatment effects with a control in a randomized block design with multiple observations per cell. Two nonparametric procedures for detecting which treatment are better than the control are proposed and compared. An example is given and the results of a Monte Carlo power study are discussed.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1399-1409
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• 2016

Nonparametric methods in randomized block design were suggested by Friedman (1937) for general alternatives and were also proposed by Page (1963) for ordered alternatives in one-way layout; in addition, K-sample rank tests for umbrella alternatives were suggested by Mack and Wolfe (1981). In this paper, we proposed a nonparametric method of umbrella alternatives for randomized block design using the aligned method proposed by Hodges and Lehmann (1962) to use block information and using placement suggested by Kim (1999). Monte Carlo simulation was also adapted to compare the power of the proposed procedure with previous methods.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.77-84
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• 2012

Mack and Skillings (1980) proposed a typical nonparametric method in a randomized block design with replications. However, this method may lose information because of the use of average observations instead of individual observations. In this paper, we proposed a nonparametric method that employed an aligned method suggested by Hodges and Lehmann (1962) under a randomized block design with replications. In addition, the comparative results of a Monte Carlo power study are presented.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1411-1419
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• 2016

Nonparametric procedures in randomized block design was proposed by Friedman (1937) as a general alternative. This method is used to find out the difference in treatment effect. It can cause a loss of inter block information using the ranking in each block. This paper proposed nonparametric procedures using an aligned method proposed by Hodges and Lehmann (1962) to reduce block information based on joint placement suggest by Jo and Kim (2013) in a randomized block design. We also compared the power of the test of the proposed procedures and established method through a Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.61-70
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• 2014

A randomized block design is a method to apply a treatment into the experimental unit of each block after dividing into several blocks with a binded homogeneous experimental unit. Jonckheere (1964) and Terpstra (1952), Page (1963), Hollander (1967) proposed various methods of ordered alternative in randomized block design. Especially, Page (1963) test is a weighted combination of within block rank sums for ordered alternatives. In this paper, we suggest a new nonparametric method expanding the Page test for an ordered alternative. A Monte Carlo simulation study is also adapted to compare the power of the proposed methods with previous methods.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.291-299
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• 2017

Mack and Skillings (1980) proposed nonparametric procedures in a randomized block design with replications as general alternatives. This method is used to find the difference in the treatment effect; however, it can cause a loss of inter block information using the ranking in each block. In this paper, we proposed new nonparametric procedures in a randomized block design with replications using an aligned method proposed by Hodges and Lehmann (1962) that used information of blocks and based on the joint placement suggest by Chung and Kim (2008). We also compared the power of the test of the proposed procedures and established a method through Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.707-717
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• 2016

Nonparametric procedures in a randomized block design was proposed by Friedman (1937) as a general alternative as well as suggested as a test for ordered alternatives by Page (1963). These methods are used for the rank of treatments in each block. In this paper, we proposed nonparametric procedures using aligned method proposed by Hodges and Lehmann (1962) to reduce among block information and based on placement suggested by Kim (1999) in a randomized block design. We also perform a Monte Carlo study to compare the empirical powers of the proposed procedures and established method.

• 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.6
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• pp.931-941
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• 2017

Typical Nonparametric methods for randomized block design with replications are two methods proposed by Mack (1981) and Mack and Skillings (1980). This method is likely to cause information loss because it uses the average of repeated observations instead of each repeated observation in the processing of each block. In order to compensate for this, we proposed a test method using linear placement statistics, which is a score function applied to the joint placement method proposed by Chung and Kim (2007). Monte Carlo simulation study is adapted to compare the power with previous methods.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.159-168
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• 1999

We introduce a new conditional signed-rank test for the tree alternatives comparing several treatments with a control in the randomized block design. We demonstrate its performance by comparing with 3 classes of signed-rank tests proposed by Park et al.(1991) in some general situations. In most cases the proposed procedure is simpler to compute and has better power than others.