E-optimal block designs under heteroscedastic model

This paper mainly studies the E-optimality of block designs under a general heteroscedastic setting. The C-matrix of a block design under a heteroscedastic setting is obtained by using generalized least squares. Some bounds for the smallest positive eigenvalue of C-matrix are obtained in some general classes of connected designs. Use of these bounds is then made to obtain certain E-optimal block designs in various classes of connected block designs.     

On the property of balance and the pattern op c-matrdc in block designs

The alternative ways of defining balance in experimental designs, e.g. variance, efficiency, and X^-1balance are discussed, A condition is derived for a design to estimate the given set of contrasts with specified variances and covariances. This condition is based upon the C-matrix of block designs. The usefulness of the results presented in the construction of designs is discussed with the help of examples.     

Admissibility in factorial designs

The notion of admissibility in factorial designs has been introduced. It has been shown that factorial designs which are binary and have a C-matrix with property A are admissible.     

Optimality in the presence of two factor interactions among the nuisance factors

Here we consider an m way heterogeneity settingin the presence of two factor interactions among the heterogeneity directions . The set of experimental units considered do not exhaust all possible level combinations of the heterogeneity directions ; but the set is such that all heterogeneity effects assumed i n the model are orthogonally estmable.In such a setting , calleda doubly balanced m-way setting , the C-matrix of the reduced normal equations for the treatment effects is derived . Universally optimal designs are obtained in the cases where the settingis (i) Completely regular or (ii) partly regular of a special type . An interesting observation is that there are situations where the universally optimal designsin the present setting are totally different from the designs known t o be universally optimal when there is no interaction effect among the heterogeneity directions. This indicates that the usual optimality criteria are sensitive to validity or otherwise of the usual assumptions of lack of interactions among heterogeneity directions.     

On some properties of the dual of a totally balanced block design

In this paper it is shown that the dual of a totally balanced block design with t = b, is also a totally balanced block design. It is shown that Fisher's inequality $\text{b≧t}$ for BIB designs, holds also for a totally balanced block design.     

CHANGE-OVER DESIGNS WITH ERRORS FOLLOWING A FIRST ORDER AUTOREGRESSIVE PROCESS

This paper deals with the problem of analysing the change over design in the context of a first order autoregressive process for the error terms. The method of maximum likelihood has been adopted for estimating treatment effects. The conditions derived for obtaining a balanced change over design show that a change over design balanced in the absence of autocorrelation is not necessarily balanced in the presence of autocorrelation. Also, it is observed that the autocorrelation co-efficient and the treatment effect when p≠0 can be tested as usual with the likelihood ratio test criterion.     

Pseudo-Youden designs balanced for intersection

If the row-column intersections of a row-column design A form a balanced incomplete block design, then A is said to be balanced for intersection. This property was originally defined for triple arrays by McSorley et al. (2005a), Section 8, where an example was presented and questions of existence were raised and discussed. We give sufficient conditions for the class of balanced grids in order to be balanced for intersection, and prove that a family of binary pseudo-Youden designs has this property.     

On the recovery of intra- and interblock information in n-ary designs

This note presents an extension of Q-method of analysis for binary designs given by Rao (1956) to n-ary balanced and partially balanced block designs. Here a linked n-ary block (LNB) design is defined as the dual of balanced n-ary (BN) design. Having a note on Yates’ (1939, 1940) method of P-analysis, we further extend the expressions for binary linked block (LB) designs given by Rao (1956) to linked n-ary block (LNB) designs which admit easy estimation of parameters for these type of all n-ary designs.     

Optimal partially balanced nested row-column designs

A partially balanced nested row-column design, referred to as PBNRC, is defined as an arrangement of v treatments in b p × q blocks for which, with the convention that p q, the information matrix for the estimation of treatment parameters is equal to that of the column component design which is itself a partially balanced incomplete block design. In this paper, previously known optimal incomplete block designs, and row-column and nested row-column designs are utilized to develop some methods of constructing optimal PBNRC designs. In particular, it is shown that an optimal group divisible PBNRC design for v = mn kn treatments in p × q blocks can be constructed whenever a balanced incomplete block design for m treatments in blocks of size k each and a group divisible PBNRC design for kn treatments in p × q blocks exist. A simple sufficient condition is given under which a group divisible PBNRC is Ψ_f-better for all f> 0 than the corresponding balanced nested row-column designs having binary blocks. It is also shown that the construction techniques developed particularly for group divisible designs can be generalized to obtain PBNRC designs based on rectangular association schemes.     

Invited Discussion Paper Resampling Methods in Sample Surveys

This article reviews the applications of three resampling methods, the jackknife, the balanced repeated replication, and the bootstrap, in sample surveys. The sampling design under consideration is a stratified multistage sampling design. We discuss the implementation of the resampling methods; for example, the construction of balanced repeated replications and approximated balanced repeated replication estimators; four modified bootstrap algorithms to generate bootstrap samples; and three different ways of applying the resampling methods in the presence of imputed missing values. Asymptotic properties of the resampling estimators are discussed for two types of important survey estimators, functions of weighted averages and sample quantiles.     

改进样本代表性的多目标追加平衡设计

本文主要讨论样本代表性的改进和多目标调查两个问题。一,本文提出了一种新的改进样本代表性多目标抽样方法,增加样本量与调整样本结构相结合的方法-追加样本的平衡设计,即通过追加样本,使得补充的样本与原来的样本组合生成新的平衡样本,相对于初始样本,减少样本与总体的结构性偏差。平衡样本是指辅助变量总量的霍维茨汤普森估计量等于总体总量真值。二,平衡样本通过选择与多个目标参数相关的辅助变量,使得一套样本对不同的目标参数而言都具有良好的代表性,进而完成多目标调查。结合2010年第六次人口分县普查数据,通过选择多个目标参数,对追加样本后的平衡样本作事后评估结果表明,追加平衡设计能够有效改进样本结构,使得样本结构与总体结构相近,降低目标估计的误差;同时也说明平衡抽样设计能够实现多目标调查,提高样本的使用效率。     

Analysis of variance of balanced fractional 2n factorial designs of resolution 2l+1

By use of the algebraic structure of the triangular multidimensional partially balanced association scheme, we present the analysis of variance and the hypotheses testing of a balanced fractional 2ⁿfactorial design of resolution 2l+1, which is derived from a balanced array of strength 2l.     

Constructions of Nested Pairwise Efficiency and Variance Balanced Designs

ABSTRACT

Nested pairwise efficiency and variance balanced designs form a new class of block designs. In this article, two methods of constructing such designs from a symmetric balanced incomplete block design are proposed with some illustrations.     

Multiphase experiments with at least one later laboratory phase. II. Nonorthogonal designs

Principles and laws that apply to nonorthogonal multiphase experiments are developed and illustrated using examples that are nonorthogonal but structure‐balanced, not structure, but first‐order, balanced or unbalanced, thus exposing the differences between the different design types. The design of such experiments using standard designs, a catalogue of designs and computer searches is exemplified. Factor–allocation diagrams are employed to depict the allocations in the examples, and used in producing the anatomies of designs or, when possible, the related skeleton‐analysis‐of‐variance tables, to assess the properties of designs. The formulation of mixed models based on them is also described. Tools used for structure‐balanced experiments are also shown to be applicable to those experiments that are not.     

On totally balanced block designs for competition effects

Competition between neighbouring units in field experiments is a serious source of bias. The study of a competing situation needs construction of an environment in which it can happen and the competing units have to appear in a predetermined pattern. This paper describes methods of constructing incomplete block designs balanced for neighbouring competition effects. The designs obtained are totally balanced in the sense that all the effects, direct and neighbours, are estimated with the same variance. The efficiency of these designs has been computed as compared to a complete block design balanced for neighbours and a catalogue has also been prepared.     

Characterization of Balanced Fractional 3 m Factorial Designs of Resolution III

We consider a fractional 3 ^m factorial design derived from a simple array (SA), which is a balanced array of full strength, where the non negligible factorial effects are the general mean and the linear and quadratic components of the main effect, and m ≥ 2. In this article, we give a necessary and sufficient condition for an SA to be a balanced fractional 3 ^m factorial design of resolution III. Such a design is characterized by the suffixes of indices of an SA.     

Cancer immunotherapy trial design with delayed treatment effect

A challenge arising in cancer immunotherapy trial design is the presence of a delayed treatment effect wherein the proportional hazard assumption no longer holds true. As a result, a traditional survival trial design based on the standard log‐rank test, which ignores the delayed treatment effect, will lead to substantial loss of statistical power. Recently, a piecewise weighted log‐rank test is proposed to incorporate the delayed treatment effect into consideration of the trial design. However, because the sample size formula was derived under a sequence of local alternative hypotheses, it results in an underestimated sample size when the hazard ratio is relatively small for a balanced trial design and an inaccurate sample size estimation for an unbalanced design. In this article, we derived a new sample size formula under a fixed alternative hypothesis for the delayed treatment effect model. Simulation results show that the new formula provides accurate sample size estimation for both balanced and unbalanced designs.     

Three-factor symmetrical balanced designs with full efficiency for main effects

Some methods for constructing balanced design for 3-factor symmetrical factorial experiments in which all the main effects are completely unconfounded by using balanced arrays and BIB designs are proposed. The method is flexible in terms of selecting block size.     

NECESSARY AND SUFFICIENT CONDITION FOR A BALANCED ARRAY OF STRENGTH 21 TO BE A BALANCED FRACTIONAL 2 FACTORIAL DESIGN OF RESOLUTION 2l

A necessary and sufficient condition for a balanced array of strength 2l to be a balanced fractional 2^m factorial design of resolution 2l is given. This design has the property that the main effects, two-factor interactions,.and (l-1)-factor interactions are estimable ignoring the (l + 1)-factor and higher order interactions, and that the covariance matrix of their estimates is invariant under any permutation of m factors. The above condition includes sufficient conditions given in earlier works of Shirakura (1976b, 1977).