THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Cultural ecosystem services (ES) are consistently recognized but not yet adequately defined or integrated within the ES framework. A substantial body of models, methods, and data relevant to cultural services has been developed within the social and behavioral sciences before and outside of the ES approach. A selective review of work in landscape aesthetics, cultural heritage, outdoor recreation, and spiritual significance demonstrates opportunities for operationally defining cultural services in terms of socioecological models, consistent with the larger set of ES. Such models explicitly link ecological structures and functions with cultural values and benefits, facilitating communication between scientists and stakeholders and enabling economic, multicriterion, deliberative evaluation and other methods that can clarify tradeoffs and synergies involving cultural ES. Based on this approach, a common representation is offered that frames cultural services, along with all ES, by the relative contribution of relevant ecological structures and functions and by applicable social evaluation approaches. This perspective provides a foundation for merging ecological and social science epistemologies to define and integrate cultural services better within the broader ES framework.

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Contributions of cultural services to the ecosystem services agenda.

Purpose: The purpose of this article is twofold: 1) introducing logistic regression (LR), a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, and 2) examining use and reporting of LR in the nursing literature. Methods: Text books on LR and research articles employing LR as main statistical analysis were reviewed. Twenty-three articles published between 2010 and 2011 in the Journal of Korean Academy of Nursing were analyzed for proper use and reporting of LR models. Results: Logistic regression from basic concepts such as odds, odds ratio, logit transformation and logistic curve, assumption, fitting, reporting and interpreting to cautions were presented. Substantial shortcomings were found in both use of LR and reporting of results. For many studies, sample size was not sufficiently large to call into question the accuracy of the regression model. Additionally, only one study reported validation analysis. Conclusion: Nursing researchers need to pay greater attention to guidelines concerning the use and reporting of LR models.

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An introduction to logistic regression: from basic concepts to interpretation with particular attention to nursing domain.

Foundations of Statistical Inference

Some remarks on the combination of independent tests

The importance of landscape in wine quality perception: An integrated approach using choice-based conjoint analysis and combination-based permutation tests

In this paper a new model validation procedure for a logistic regression model is presented. At first, we illustrate a brief review of different techniques of model validation. Next, we define a number of properties required for a model to be considered "good", and a number of quantitative performance measures. Lastly, we describe a methodology for the assessment of the performance of a given model by using an example taken from a management study.

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Model performance analysis and model validation in logistic regression

Purpose – Packaging features have been shown to be of great importance for the consumer final choice of fresh products (Silayoi and Speece, 2007). Packaging is an extrinsic attribute, which consumers tend to rely on, when relevant intrinsic attributes of the product are not available. In the current literature, studies on the influences of packaging features on consumer preferences are mainly related to classical preference evaluation methods like conjoint analysis (CA). The purpose of this paper is to apply both CA and the less known combination of uniform discrete and shifted binomial distributions (CUB) models to food packaging evaluations. Design/methodology/approach – Starting from a real case study in this field, along with CA, the author apply CUB models (Iannario and Piccolo, 2010) as a useful tool to evaluate preferences. CUB models can grasp some psychological characteristics of consumers related to the “feeling” toward packaging attributes and related to an inherently “uncertainty” that affects...

Consumer preferences in food packaging: cub models and conjoint analysis

/pdf/consumer-preferences-in-food-packaging-cub-models-and-2uuivrsvs4.pdf

Stochastic dominance problems in testing for ordered categorical variables are of specific interest in performance analysis, because they are frequently encountered in practice and present distinctive difficulties, especially within the framework of likelihood ratio tests. Until now, the literature has essentially considered the univariate case, and several solutions have been proposed to cope with it, most of which are based on restricted maximum likelihood ratio tests. These solutions are generally criticised, because the degree of accuracy of their asymptotic null and alternative distributions is difficult to assess and characterise. In this paper, we propose a new exact solution based on a simultaneous analysis of a finite set of sampling moments of ranks, or general scores, assigned to ordered classes and processed within a permutation approach.

Rosa Arboretti Giancristofaro

Papers

The importance of landscape in wine quality perception: An integrated approach using choice-based conjoint analysis and combination-based permutation tests

Model performance analysis and model validation in logistic regression

Consumer preferences in food packaging: cub models and conjoint analysis

Consumer preferences in food packaging: cub models and conjoint analysis

Moment-based multivariate permutation tests for ordinal categorical data