Construction and Analysis of an Augmented Lattice Square Design

Augmented designs are useful for screening experiments involving large numbers of new and untried treatments. Since resolvable row‐column designs are useful for controlling extraneous variation, it is desirable to use such designs for the check or standard treatments to construct augmented lattice square experiment designs. A simple procedure is described for constructing such designs using c = 2k and c = 3k check treatments and n = rk(k ‐— 2) and n = rk(k — 3) new treatments, respectively, r being the number of complete blocks. A trend analysis for these designs, which allows for solutions of fixed effects, is presented. The random effects case is also discussed. A SAS computer code and the output from this code illustrated with a small numerical example are available from the author.     

A note on the Design of Unreplicated Trials

One approach to the design of early generation trials is to have a number of replicated check varieties and a larger number of unreplicated or new varieties. For such trials we define the class of α–α‐designs as an extension to the augmented lattice square designs of Federer (2002). Efficient latinized α–α‐designs can be conveniently constructed using the design generation package CycDesigN.     

Construction of Resolvable Designs with Nested Treatment Structure

The construction of resolvable incomplete block and row-column designs is investigated when the treatments have a nested structure. Some theoretical results are derived for lattice designs. Efficient designs for unequal-sized treatment groups are obtained by defining a multiple objective function and carrying out a computer search using an interchange algorithm.     

Extending the loop design for two-channel microarray experiments

The loop design of Kerr and Churchill is a clever application of incomplete blocks of size 2 to two-channel microarray experiments. In this paper, we extend the loop design to include more replicates, biological and technical replication, multi-factor experiments, and blocking. Loop and extended loop designs are shown to be more efficient than the reference design for any given number of arrays. We also show that adding new treatments to a loop design requires the same number of additional arrays as adding treatments to a reference design, with a greater gain in power. Given the flexibility of extended loop designs and their power, we propose that these should be the designs of choice for most experiments using two-channel microarrays.     

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.     

An Upper Bound for the Number of Treatments Common to any Set of Blocks of Certain PBIB Designs

In this paper an upper bound for the number of treatments common to any set of blocks of group divisible, triangular, L₂ and rectangular designs is derived.     

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.     

Direct Sum Matrix Game with Prisoner's Dilemma and Snowdrift Game

A direct sum form is proposed for constructing a composite game from two games, prisoner''s dilemma and snowdrift game. This kind of direct sum form game is called a multiple roles game. The replicator dynamics of the multiple roles game with will-mixed populations is explored. The dynamical behaviors on square lattice are investigated by numerical simulation. It is found that the dynamical behaviors of population on square lattice depend on the mixing proportion of the two simple games. Mixing SD activities to pure PD population inhibits the proportion of cooperators in PD, and mixing PD activities to pure SD population stimulates the proportion of cooperators in SD. Besides spatial reciprocity, our results show that there are roles reciprocities between different types of individuals.     

Increasing Biomass Production on Limited Land Area Through an Optimal Planting Arrangement

Planting density is a primary consideration in silviculture; however, planting arrangement is often ignored. Most, if not all, forest plantations are arranged in rectangular or square lattices (i.e., grids). Using a simple mathematical model, we investigate the potential influence of planting arrangement on planting density, biomass yield, and rotation period by assuming that efficiently arranging trees is similar to packing congruent circles on a plane. The hexagonal lattice achieves the densest circle packing on a plane; therefore, a hexagonal or triangular lattice arrangement of stems provides the highest planting density for a given spacing. Using packing density to quantify arrangement efficiency, tree crowns in a hexagonal lattice fill approximately 90.7% of available area at initial canopy contact, while tree crowns in a square lattice fill approximately 78.5% of available area at initial canopy contact. The hexagonal lattice permits about a 15% higher density than the square lattice, which allows canopy closure to occur earlier without any change in individual tree growth. Short rotation woody crop (SRWC) systems are excellent candidates under the model’s assumptions of level stand with even-age monoculture. If belowground resources are non-limiting, a hexagonal lattice arrangement shortens rotation period and thus optimizes the biomass yield per land area over time. Higher productivity over time is central to sustainable and efficient use of limited area for bioenergy and biomass products.     

Non-Iterative Least Squares Estimation of Missing Values in Hyper-Graeco-Latin Square Designs

In this paper an attempt has been made to obtain explicit expressions for the estimators of the several missing values in hyper-graeco-latin square designs. Further it has been shown that the estimates of the missing values in latin square designs and graeco-latin square designs are obtained as a particular case of the estimates of the missing values in hyper-graeco-latin square designs.     

Consistent Strategy Updating in Spatial and Non-Spatial Behavioral Experiments Does Not Promote Cooperation in Social Networks

The presence of costly cooperation between otherwise selfish actors is not trivial. A prominent mechanism that promotes cooperation is spatial population structure. However, recent experiments with human subjects report substantially lower level of cooperation then predicted by theoretical models. We analyze the data of such an experiment in which a total of 400 players play a Prisoner''s Dilemma on a square lattice in two treatments, either interacting via a fixed square lattice (15 independent groups) or with a population structure changing after each interaction (10 independent groups). We analyze the statistics of individual decisions and infer in which way they can be matched with the typical models of evolutionary game theorists. We find no difference in the strategy updating between the two treatments. However, the strategy updates are distinct from the most popular models which lead to the promotion of cooperation as shown by computer simulations of the strategy updating. This suggests that the promotion of cooperation by population structure is not as straightforward in humans as often envisioned in theoretical models.     

LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research

One of the most important steps in biomedical longitudinal studies is choosing a good experimental design that can provide high accuracy in the analysis of results with a minimum sample size. Several methods for constructing efficient longitudinal designs have been developed based on power analysis and the statistical model used for analyzing the final results. However, development of this technology is not available to practitioners through user-friendly software. In this paper we introduce LADES (Longitudinal Analysis and Design of Experiments Software) as an alternative and easy-to-use tool for conducting longitudinal analysis and constructing efficient longitudinal designs. LADES incorporates methods for creating cost-efficient longitudinal designs, unequal longitudinal designs, and simple longitudinal designs. In addition, LADES includes different methods for analyzing longitudinal data such as linear mixed models, generalized estimating equations, among others. A study of European eels is reanalyzed in order to show LADES capabilities. Three treatments contained in three aquariums with five eels each were analyzed. Data were collected from 0 up to the 12th week post treatment for all the eels (complete design). The response under evaluation is sperm volume. A linear mixed model was fitted to the results using LADES. The complete design had a power of 88.7% using 15 eels. With LADES we propose the use of an unequal design with only 14 eels and 89.5% efficiency. LADES was developed as a powerful and simple tool to promote the use of statistical methods for analyzing and creating longitudinal experiments in biomedical research.     

Treatment allocation for nonlinear models in clinical trials: the logistic model

Many clinical trials have a binary outcome variable. If covariate adjustment is necessary in the analysis, the logistic-regression model is frequently used. Optimal designs for allocating treatments for this model, or for any nonlinear or heteroscedastic model, are generally unbalanced with regard to overall treatment totals and totals within strata. However, all treatment-allocation methods that have been recommended for clinical trials in the literature are designed to balance treatments within strata, either directly or asymptotically. In this paper, the efficiencies of balanced sequential allocation schemes are measured relative to sequential Ds-optimal designs for the logistic model, using as examples completed trials conducted by the Eastern Cooperative Oncology Group and systematic simulations. The results demonstrate that stratified, balanced designs are quite efficient, in general. However, complete randomization is frequently inefficient, and will occasionally result in a trial that is very inefficient.     

On the Characterization and Software Implementation of General Protein Lattice Models

Abstract models of proteins have been widely used as a practical means to computationally investigate general properties of the system. In lattice models any sterically feasible conformation is represented as a self-avoiding walk on a lattice, and residue types are limited in number. So far, only two- or three-dimensional lattices have been used. The inspection of the neighborhood of alpha carbons in the core of real proteins reveals that also lattices with higher coordination numbers, possibly in higher dimensional spaces, can be adopted. In this paper, a new general parametric lattice model for simplified protein conformations is proposed and investigated. It is shown how the supporting software can be consistently designed to let algorithms that operate on protein structures be implemented in a lattice-agnostic way. The necessary theoretical foundations are developed and organically presented, pinpointing the role of the concept of main directions in lattice-agnostic model handling. Subsequently, the model features across dimensions and lattice types are explored in tests performed on benchmark protein sequences, using a Python implementation. Simulations give insights on the use of square and triangular lattices in a range of dimensions. The trend of potential minimum for sequences of different lengths, varying the lattice dimension, is uncovered. Moreover, an extensive quantitative characterization of the usage of the so-called “move types” is reported for the first time. The proposed general framework for the development of lattice models is simple yet complete, and an object-oriented architecture can be proficiently employed for the supporting software, by designing ad-hoc classes. The proposed framework represents a new general viewpoint that potentially subsumes a number of solutions previously studied. The adoption of the described model pushes to look at protein structure issues from a more general and essential perspective, making computational investigations over simplified models more straightforward as well.     

Efficient algorithms for optimal designs with correlated observations in pharmacokinetics and dose-finding studies

Random effects models are widely used in population pharmacokinetics and dose-finding studies. However, when more than one observation is taken per patient, the presence of correlated observations (due to shared random effects and possibly residual serial correlation) usually makes the explicit determination of optimal designs difficult. In this article, we introduce a class of multiplicative algorithms to be able to handle correlated data and thus allow numerical calculation of optimal experimental designs in such situations. In particular, we demonstrate its application in a concrete example of a crossover dose-finding trial, as well as in a typical population pharmacokinetics example. Additionally, we derive a lower bound for the efficiency of any given design in this context, which allows us on the one hand to monitor the progress of the algorithm, and on the other hand to investigate the efficiency of a given design without knowing the optimal one. Finally, we extend the methodology such that it can be used to determine optimal designs if there exist some requirements regarding the minimal number of treatments for several (in some cases all) experimental conditions.     

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.     

Levene tests of homogeneity of variance for general block and treatment designs

This article develops a weighted least squares version of Levene's test of homogeneity of variance for a general design, available both for univariate and multivariate situations. When the design is balanced, the univariate and two common multivariate test statistics turn out to be proportional to the corresponding ordinary least squares test statistics obtained from an analysis of variance of the absolute values of the standardized mean-based residuals from the original analysis of the data. The constant of proportionality is simply a design-dependent multiplier (which does not necessarily tend to unity). Explicit results are presented for randomized block and Latin square designs and are illustrated for factorial treatment designs and split-plot experiments. The distribution of the univariate test statistic is close to a standard F-distribution, although it can be slightly underdispersed. For a complex design, the test assesses homogeneity of variance across blocks, treatments, or treatment factors and offers an objective interpretation of residual plots.     

A TEST AND REVIEW OF THE ROLE OF EFFECTIVE POPULATION SIZE ON EXPERIMENTAL SEXUAL SELECTION PATTERNS

Experimental evolution, particularly experimental sexual selection in which sexual selection strength is manipulated by altering the mating system, is an increasingly popular method for testing evolutionary theory. Concerns have arisen regarding genetic diversity variation across experimental treatments: differences in the number and sex ratio of breeders (effective population size; N_e ) and the potential for genetic hitchhiking, both of which may cause different levels of genetic variation between treatments. Such differences may affect the selection response and confound interpretation of results. Here we use both census-based estimators and molecular marker-based estimates to empirically test how experimental evolution of sexual selection in Drosophila pseudoobscura impacts N_e and autosomal genetic diversity. We also consider effects of treatment on X-linked N_e s, which have previously been ignored. Molecular autosomal marker-based estimators indicate that neither N_e nor genetic diversity differs between treatments experiencing different sexual selection intensities; thus observed evolutionary responses reflect selection rather than any confounding effects of experimental design. Given the increasing number of studies on experimental sexual selection, we also review the census N_e s of other experimental systems, calculate X-linked N_e , and compare how different studies have dealt with the issues of inbreeding, genetic drift, and genetic hitchhiking to help inform future designs.     

Statistical Analyses for Multistage Experiment Designs

Suppose that t experiments are conducted simultaneously on the same set of experimental units. For example, suppose that t mutually orthogonal latin square experiment designs are used for the t experiments on n² experimental units. Statistical literature is voluminous on construction of such designs, but contains relatively little and incomplete results on statistical analyses for such designs. Six statistical analyses are presented for a pair of orthogonal latin square experiment designs. Then, the methods are generalized for t mutually orthogonal experiment designs. The results are also extended to a set of t mutually balanced Youden experiment designs.     

Cryo-electron tomography of clathrin-coated vesicles: structural implications for coat assembly

Clathrin-coated vesicles mediate vesicular traffic in cells. Three-dimensional image reconstructions of homogenous populations of in vitro assembled clathrin coats have yielded a molecular model for clathrin and its interactions with some of its partners. The intrinsic averaging required for those calculations has precluded detailed analysis of heterogeneous populations of clathrin-coated vesicles isolated from cells. We have therefore used cryo-electron tomography to study the lattice organization of individual clathrin-coated vesicles and the disposition of the captured vesicle with respect to the surrounding coat. We find a wide range of designs for the clathrin lattice, with different patterns of pentagonal, hexagonal, and occasionally heptagonal facets. Many coats, even smaller ones, enclose membrane vesicles, which are generally offset from the center of the clathrin shell. The electron density distribution between the coat and the underlying vesicle is not uniform, and the number of apparent contacts that anchor the clathrin lattice to the vesicle membrane is significantly less than the number of clathrin heavy chains in the assembly. We suggest that the eccentric position of the vesicle reflects the polarity of assembly, from initiation of coat formation to membrane pinching.