• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.171-174
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• 2002

In this paper, diallel crosses block designs for control versus test comparisons among the lines are proposed. These designs are constructed by using partially balanced incomplete block designs with C-properties. Also, the efficiencies of the diallel crosses block designs obtained through this method are tabulated for number of lines 24 or less.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.181-189
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• 2005

This paper suggest a method of inclusion probability proportional to size sampling that provides a non-negative and stable variance estimator. The sampling procedure is quite simple and flexible since a sampling design is easily obtained using mathematical programming. This scheme appears to be preferable to Nigam, Kumar and Gupta's (1984) method which uses a balanced incomplete block designs. A comparison is made with their method through an example in the literature.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.175-184
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• 2002

In this paper, diallel crosses block designs for control versus test comparisons among the lines are proposed. These block designs are constructed by using partially balanced incomplete block designs with C-properties. Also, the efficiencies of the diallel crosses block designs obtained through this method are tabulated for number of lines 22 or less.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.53-61
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• 2002

In this paper we proposed the method of the block designs for diallel crosses when inbred lines are divided into two groups. These block designs are derived by using kornecker product designs with two balanced incomplete block designs, and their efficiency factor evaluated. A table of diallel crosses for up to p$_1$$\leq$15 lines, p$_2$$\leq$15 lines in each set is also provided.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.347-354
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• 2015

This paper deals with a method for intrablock anlaysis of balanced incomplete block designs on the basis of projections under the assumption of mixed effects model. It shows how to construct a model at each step by the stepwise procedure and discusses how to use projection for the analysis of intrablock. Projections are obtained in vector subspaces orthogonal to each other. So the estimates of the treatment effects are not affected by the block effects. The estimability of a parameter or a function of parameters is discussed and eigenvectors are dealt for the construction of estimable functions.

• The Korean Journal of Applied Statistics
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• v.3 no.2
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• pp.55-77
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• 1990

In this paper we descuss some E-optimal block designs having unequal block sizes, and give a table of E-optimal designs with 2 different block sizes which can be constructed using the method described in Theorem 3. 2, Theorem 3. 4 and Theorem 3. 5 proved by Lee and Jacroux (1987). All of source designs used are Group Divisible designs which can be found in Clathworthy(1973) or Balanced Incomplete block designs in Raghavarar(1971).

• Journal of the Korean Statistical Society
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• v.15 no.2
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• pp.118-126
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• 1986

The relationships between combined estimators and generalized least squares estimators in block designs are reviewed. Here combined estimators mean the best linear combination of intrablock and interblock estimaters. It is well known that only for balanced incomplete block designs the combined estimators of Yates and of the generalized least squares estimators give the same result. In this paper, a general form of the combined estimators for treatment effects is derived and it can be seen that such estimators are equivalent to the generalized least squares estimators.

• Journal of the Korean Data and Information Science Society
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• v.1
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• pp.7-33
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• 1990

Bechhofer and Tamhane(1981) developed a theory of optimal incomplete block designs for comparing several treatments with a control. This class of designs is appropriate for comparing simultaneously $p{\geq}2$ test treatments with a control treatment (the so-called multiple comparisons with a control (MCC) problem) when the observations are taken in incomplete blocks of common size $K{\<}p+1$. In this paper we want to extend to partially BTIB designs with two associate classes for the MCC problem. We propose a new class of incomplete block designs that are partially balanced with respect to test treatments. Because the class of designs that we consider is larger than the class of designs in Bechhofer and Tamhane and provides us with designs that improve on the optimal designs in their class. We shall use the abbreviation PBTIB to refer to such designs. We study their structure and give some methods of construction. Also we describe a procedure for making exact joint confidence statements for the MCC problem in PBTIB Designs with two associate classes. We study Optimality, Admissibility considerations in PBTIB designs with two associate classes.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.151-158
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• 2015

This paper discusses how to use projections for the analysis of data from balanced incomplete block designs. A model is suggested as a matrix form for the interblock analysis. A second set of treatment effects can be found by projections from the suggested interblock model. The variance and covariance matrix of two estimated vectors of treatment effects is derived. The uncorrelation of two estimated vectors can be verified from their covaraince structure. The fitting constants method is employed for the calculation of block sum of squares adjusted for treatment effects.

• Journal of the Korean Statistical Society
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• v.3 no.2
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• pp.85-101
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• 1974

In a Balanced Factorial Experiments (BFE) with n factors $F_1, F_2,\cdots,F_n$ at $m_1, m_2,\cdots,m_n$ levels respectively, Shah [15] has considered the following association scheme: the two treatments are the $(P_1, P_2,\cdot,P_n)$th associates, where $p_i=1$ if the ith factor occurs at the same level in both treatments and $p_i=0$ otherwise; $\lambda_{(p_1,p_2,\cdots,p_n)}$ will denote the number of times these treatments occur together in a block. He has showed that a BFE is partially Blanced Incomplete Block(PBIB) design with repsect to the above association scheme. Kurjian and Zelan [6] have proved that factorial designs possessing a Property A (a particular structure for their matrix NN') are factorially balanced.