1,720,986 research outputs found
A survey and evaluation of methods for determination of combinatorial equivalence of factorial designs
No full textEquivalent factorial designs have identical statistical properties for estimation of factorial contrasts and for model fitting. Non-equivalent designs, however, may have the same statistical properties under one particular model but different properties under a different model. In this paper, we describe known methods for the determination of equivalence or non-equivalence of two-level factorial designs, whether they be regular factorial designs, non-regular orthogonal arrays, or have no particular structure. In addition, we evaluate a number of potential fast screening methods for detecting non-equivalence of designs. Although the paper concentrates mainly on symmetric designs with factors at two levels, we also evaluate methods of determining combinatorial equivalence and non-equivalence of three-level designs and indicate extensions to larger numbers of levels and to asymmetric designs
Comparison of group screening strategies for factorial experiments
No full textFactor screening is an important first step in many industrial experiments where a large number of factors potentially influence a response. The purpose of screening is to identify those few factors which have a substantive influence (that is, are active) and therefore, require further investigation. This paper provides a simulation tool for comparing two-stage group screening strategies where both design and noise factors may be under study. The strategies investigated are classical group screening, in which only main effects are considered at the first stage of the experiment, and an alternative strategy of screening for two-factor interactions as well as main effects.An algorithm is described which allows the user to simulate, and hence to compare, the strategies under different selections of designs and different group sizes for the stage 1 experiment, and for different probabilities of active effects. A detailed example of the use of the algorithm shows how an appropriate strategy can be chosen based on two criteria. These criteria consider the proportion of active factorial effects that are incorrectly screened out at the first-stage experiment, and the average number of observations needed for the entire experiment
Detection of interactions in experiments on large numbers of factors
No full textOne of the main advantages of factorial experiments is the information they can offer on interactions. When there are many factors to be studied, some or all of this information is often sacrificed in order to keep the size of the experiment economically feasible. Two strategies for group screening are presented for a large number of factors, over two stages of experimentation, with particular emphasis on the detection of interactions. One approach estimates only main effects at the first stage (classical group screening), whilst the other new method (interaction group screening) estimates both main effects and key two factor interactions at the first stage. Three criteria are used to guide the choice of screening technique, and also the size of the groups of factors for study in the first stage experiment. The criteria seek to minimise the expected total number of observations in the experiment, the probability that the experiment size exceeds a pre-specified target, and the proportion of active individual effects which are not detected. In order to implement these criteria, results are derived on the relationship between the grouped and individual factorial effects, and the probability distributions of the numbers of grouped factors whose main effects or interactions are declared active at the first stge. Examples are used to illustrate the methodology, and some issues and open questions for the practical implementation of the results are discussed
Further properties of mixture designs for five components in orthogonal blocks.
No full textOrthogonally blocked experimental designs for mixtures of five ingredients, formed from Latin squares, were previously discussed by Prescott et al. Here, we extend this development by studying the properties of three classes of possible designs, with recommendations on their practical application. Restrictions on the design classes are explored and D-optimal (within the classes) versions are identified. Remarks on general D-optimality conclude the paper
Mixture experiments: ILL-conditioning and quadratic model specification
No full textWell-conditioned models are important, particularly for practitioners who work with regression models for mixture experiments where parameter estimates are individually meaningful. In this article we investigate conditioning in second-order mixture models, using variance inflation factors, maximum and minimum eigenvalues of the information matrix and condition numbers to assess conditioning. A range of equivalent mixture models that lie "between" the Scheffé model (S-model) and the Kronecker model (K-model) is examined, and pseudocomponent transformations for lower bounds (L-pseudocomponents) and upper bounds (U-pseudocomponents) are also discussed. We prove that the maximum eigenvalue for the information matrix for the K-model is always smaller than that for any other model in the above range. We recommend in practice the use of the K-model, to reduce ill-conditioning, and the appropriate use of pseudocomponents
A critical assessment of two-stage group screening through industrial experimentation
No full textScreening is the process of sifting through a set of factors through experimentation to determine the few important factors that have a substantial effect on a response. When the set of factors is large and interactions are anticipated, screening methods using single fractional factorial designs may require too many observations to be feasible. The methodology of two-stage group screening has been suggested as an alternative. This article gives the first description of practical aspects involved in running a two-stage group screening experiment for investigating interactions. Issues involved in the design and analysis of such an experiment are discussed in the context of a study run at Jaguar Cars on cold start optimization. The analysis of this experiment provides insight into how group screening works in practice and how the factorial effects of the individual factors relate to those of the grouped factors. Elicitation of information from subject specialists, choice of factor groups, and selection of designs for two-stage group screening are discussed. Through the analysis of the experimental data, it is shown that the process of group screening can provide an efficient method of detecting interactions among large numbers of factors
Nested changeover designs.
No full textNested changeover designs are described for experiments in which subjects are required to perform a series of tasks (levels of a factor B) under a given set of experimental conditions in any one session. The conditions (levels of a factor A) are changed from one session to another. Within each session, carryover effects may occur. This paper defines a class of nested changeover designs which are universally optimal for estimating the direct effects of the treatment combinations when observations are independent and identically distributed. A subclass is identified which has the additional property of universal optimality for estimating the carryover effects of factor B. Designs which require fewer resources, and yet retain some optimality properties, are also investigated
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
- …
