Construction of Partially Balanced Incomplete Block Designs with Nested Rows and Columns

A number of methods of construction of partially balanced incomplete block designs with nested rows and columns are developed and new balanced incomplete block designs with nested rows and columns are obtained as a by-product.     

Designs Suited for Varietal Trials with Multiple Basals

DAS (1960) gave a method of construction of confounded balanced asymmetrical factorial designs of the type v × 2² by using BIB designs. In the present paper a method has been given for construction of balanced asymmetrical factorial designs of the type (v–t) × 2² by using truncated balanced incomplete block designs obtainable by omitting t treatments. Likewise, partially balanced asymmetrical factorial designs can also be obtained by omitting any particular treatment alongwith its first or second associate treatments from the v treatments of a PBIB design. We can get a large number of new designs not available in literature through this technique. These designs are well suited for varietal trials with multiple basals.     

Small Sample Properties of Rank Tests for Incomplete Unbalanced Designs

A rank test is presented for analysis of incomplete unbalanced designs, i.e. for designs that may have been originally planned to be either balanced or unbalanced and where some observations may be missing at random. This test is a modification of the procedure of Benard and van El-teren (1953) based on a generalization of block weights proposed by Prentice (1979). It is compared with the tests of Haux, Schumacher, and Weckesser (1984) and Rai (1987). For incomplete or unbalanced designs with more than two treatments the quadratic forms proposed by these authors are proven to be invalid for small sample sizes, except for special cases. A necessary condition is given for test statistics to be valid also for small samples.     

New Constructions of BIB Designs

A method of construction of certain balanced incomplete block (BIB) designs is defined from which we get new series of BIB designs.     

A Simple Approach to Analyse Non-Orthogonal Data

The present paper deals with an alternative and simple procedure to analyse the non-orthogonal data. The procedure is general in nature but has some advantages for the non-orthogonal data due to some missing observations. The procedure is applied to (i) two way classification with unequal number of observations per cell; (ii) randomized block designs with some missing observations and (iii) balanced incomplete block designs and also illustrated with the help of numerical examples.     

Analysis of data from incomplete block designs

This paper presents an organized solution to the problem of computing inter- and intrablock analyses of incomplete block designs, based on the modified maximum likelihood principle proposed by Patterson and Thompson (1971, Biometrika 58, 545-554). The calculations are set out to be easily programmed on a microcomputer. The method is attractive because it is simple, yet sufficiently general to handle a wide class of designs, including partially balanced incomplete block designs, designs with unequal block sizes, designs with missing values, and generally unbalanced split-plot experiments.     

On the Construction of Balanced and Partially Balanced Ternary Design

A method of constructing balanced and partially balanced ternary designs from balanced and partially balanced incomplete block designs, respectively, and two methods of constructing partially balanced ternary designs from association schemes are obtained. Two new and efficient balanced ternary designs having K < V and R ≦ 20 are obtained by the first method.     

On the PBB Designs for Multiresponse Experiments

We present the idea of using multiresponse incomplete block designs when not all responses can be observed in all experimental units. For a special class of such designs, in which partial designs are PBB designs, a method for estimating natural treatment contrast is given. We also consider the problem of testing the hypotheses concerning the natural and any estimable treatment contrasts. For testing this hypothesis the Wald statistics, being asymptotically chi-square distributed, is proposed.     

Universal Optimality of Nearest Neighbour Balanced Block Designs using Second Order Correlated Models

Block designs for observations correlated in one dimension are investigated. Santharam and Ponnusamy (1995) investigated the universal optimality of Nearest Neighbour balanced block designs (NNBD) using first order correlated models (AR(1), MA(1) and ARMA(1,1)). In this article we have investigated the universal optimality of NNBD using second order correlated models (ar(2), and MA (2)).     

A Simple Construction Procedure for Eesolvable Incomplete Block Designs for any Number of Treatments

A simple, straightforward procedure, which requires no special tables or generators, is presented for constructing resolvable incomplete block designs for v=pk, v=p²k, …, treatments, for k≥p, in incomplete blocks of size k. Also, it is shown, how to obtain incomplete block designs for any v in blocks of size k and k+1. The procedure allows construction of balanced incomplete block designs for p = k a prime number. For p = n not a prime number, incomplete block designs can be obtained by the procedure, but are not balanced. However, for p_s being the smallest prime factor of n, p_s + 1 for v = n², p_s²+ p_s + 1 for v = n³, …, arrangements can be obtained for which the occurrence of any treatment pair in the blocks is either zero or one. This is called a zero-one concurrence design. Procedures are described for obtaining additional zero-one concurrence arrangements. It is shown that the efficiency of these designs is maximum. Both intra-block and inter-block analyses are described.     

FACTORS INFLUENCING THE EFFICIENCY OF INCOMPLETE BLOCK DESIGNS IN SENSORY EVALUATION EXPERIMENTS

The efficiencies of incomplete block designs were investigated by comparing two hundred and twenty eight analyses from eleven trials using hedonic scales with corresponding randomized complete block analyses. Of the ten explanatory factors examined, only the panelist, the product type, the number of samples per session and the average score of the data had an effect on the efficiency of incomplete block designs. The effect of product type was attributed to influences of produce consumed outside the trial, and the effect of the data mean reflected decreased conscientiousness with products the panelists disliked. With three and four samples per session, incomplete block designs were 31 % and 2 % more efficient, respectively, than randomized complete block designs. When five or more samples were tested, the incomplete block designs were markedly less efficient. The practical implications of all these effects on experimental design are discussed.     

Efficient two-sample designs for microarray experiments with biological replications

In the last years, biostatistical research has begun to apply linear models and design theory to develop efficient experimental designs and analysis tools for gene expression microarray data. With two-colour microarrays, direct comparisons of RNA-targets are possible and lead to incomplete block designs. In this setting, efficient designs for simple and factorial microarray experiments have mainly been proposed for technical replicates. But for biological replicates, which are crucial to obtain inference that can be generalised to a biological population, this question has only been discussed recently and is not fully solved yet. In this paper, we propose efficient designs for independent two-sample experiments using two-colour microarrays enabling biologists to measure their biological random samples in an efficient manner to draw generalisable conclusions. We give advice for experimental situations with differing group sizes and show the impact of different designs on the variance and degrees of freedom of the test statistics. The designs proposed in this paper can be evaluated using SAS PROC MIXED or S+/R lme.     

Planning incomplete block experiments when treatments are genetically related

Selection trials in plant and animal breeding, in incomplete blocks, are described by linear models with random effect parameters associated with treatments with known genetic covariance structure. It is now well known that the information on relatives can improve the analysis and many extensions of this model have been proposed, but no studies have been done on the consequences of this genetical relatedness among treatments for the optimality of block designs. Using a suitable optimality criterion, we show that the knowledge on relatedness may imply that the optimal design is not in the class of designs which are optimal for unrelated treatments. Implications for practical applications are discussed.     

The Analysis of Partial Diallel Crosses

The analysis of offsprings from the partial diallel crosses is presented. In considered type of crossing, p parental forms into H separate groups are devided. Single crosses among parental forms, from separate groups only, are performed. The analysis for experiments laid out in efficiency balanced block designs is given.     

A model-independent approach to the theory of experimental designs and a special discussion of bib. i general definition and designs with one or two block factors

Experimental designs are definded by introducing an assignment matrix Z. It is shown by block designs and double block designs that using Z or an operator on Z otherwise defined, well known designs can be got as special cases. Till now we didn' find an experimental design which could not be defined by our matrix Z. The definitions of properties of experimental designs can be given independently of the model of the statistical analysis. This is shown for the property of balance of block designs.     

A Note on Block Designs with Nested Rows and Columns

Block designs with nested rows and columns have been introduced by Singh and Dey (1979). This note gives some results regarding the total relative loss of information and patterns of efficiency balanced block designs with nested rows and columns in variable replications of treatments.     

The potential use of artificially produced monozygotic twins for comparative experiments

The uniformity of twins has been examined by assembling estimates of the intraclass correlation coefficient (rho(I)) available in the literature for a variety of parameters studied in cattle monozygotic twins and human dizygotic and monozygotic twins. The values of rho(I) vary considerably between parameters. In human monozygotic twins rho(I) is always larger compared to that found in dizygotic twins. There is insufficient evidence to determine whether artificial monozygotic twins are more uniform than natural monozygotic twins. A new measure of twin uniformity, given by T (3) = 1 (1-rho (I)) , is introduced. In practice 2T(3) gives the number of animals chosen at random that one member of a twin pair can replace without loss of statistical efficiency. A useful class of experimental designs for the exploitation of twin uniformity is incomplete block designs. These designs are defined by (v, k, b), where v is the number of treatments to be compared, k = 2, and b is the number of twin pairs. Each design has an associated efficiency (E). Provided rho(I)>1-E, an incomplete block design will be advantageous. In general, when only a few twin pairs are available, this relation will only hold for monozygotic and not dizygotic twins. Suitable arrangements of treatment comparisons for designs (3,2,8), (4,2,9), (5,2,10), (6,2,11) are presented.     

EXTENDED STATISTICAL ANALYSIS OF RANKED DATA FROM BALANCED INCOMPLETE BLOCK AND PAIRED COMPARISON DESIGNS

The usual Durbin analysis for ranked data obtained from a balanced incomplete block design is extended to allow for (1) dispersion effects, (2) a predetermined ordering of products and (3) more general trends. An application to paired comparison data is given. Calculation of p-values via Monte Carlo simulation is suggested.     

A Simple Procedure for Constructing Experiment Designs with Incomplete Blocks of Sizes 2 and 3

In order to maximize control of heterogeneity within complete blocks, an experimenter could use incomplete blocks of size k = 2 or 3. In certain situations, incomplete blocks of this nature would eliminate the need for such spatial types of analyses as nearest neighbor. The intrablock efficiency factors for such designs are relatively low. However, with recovery of interblock information, FEDERER and SPEED (1987) have presented measures of design efficiency factors which demonstrate that efficiency factors approach unity for certain ratios of the intrablock and interblock variance components. Hence with recovery of interblock information, even incomplete block designs with k = 2 or 3 have relatively high efficiency factors. The reduction in the intrablock error variance over the complete block error variance in many situations will provide designs with high efficiency. A simple procedure for constructing incomplete blocks of sizes 2 and 3 is presented. It is shown how to obtain additional zero-one association confounding arrangements when v = 4 t, t an integer, and for v = pk, k ≤ p. It is indicated how to do the statistical analysis for these designs.     

Impact of mating design on selection response in Brassica rapa L.

The impact of four mating designs on selection response for leaf area was assessed at four different population sizes, using fast-cycling Brassica rapa L. Mating designs were either balanced (partial diallel or pair mating) or unbalanced (factorial mating designs with either one or two testers). When balanced, the mating designs required different numbers of crossings for the same number of parents: the partial diallel design, in the configuration retained here, required three times as many crossings as pair mating. Population sizes were 4, 8, 16, and 32. The percentage of selected individuals was kept constant at 25%. Despite an average estimated heritability around 0.4, the overall response to selection after five generations was fairly weak in all three replicates. For a given population size, selection response was larger under balanced mating designs than under unbalanced ones. There was no difference among balanced mating designs. Both results indicate that effective population size is more important than population size or the number of crossings in maintaining genetic gain.