Sampling distributions of kruskal's measure of stress for an asymmetric matrix

In the past ten years multidimensional scaling of nonmetric data has been widely applied in behavioral and business research. This paper investigates the asymmetric data matrix and develops stress distributions based upon a null hypothesis of equal like­lihood in the ranking of a set of proximities.     

Investigating call record data using sequence analysis to inform adaptive survey designs

Researchers have become increasingly interested in better understanding the survey data collection process in interviewer-administered surveys. However, tools for analysing paradata capturing information about field processes, also called call record data, are still not yet fully explored. This paper introduces sequence analysis as a simple tool for investigating such data with the aim of better understanding and improving survey processes. A novel approach is to use sequence analysis within interviewers, which allows the identification of unusual interviewer calling behaviours, and may provide guidance on interviewer performance. Combining the technique with clustering, optimal matching and multidimensional scaling, the method offers a way of visualising, displaying and summarising complex call record data. The method is introduced to inform survey management and survey monitoring. The method is hence informative for adaptive survey designs and will help to identify unusual behaviour and outliers and to improve survey processes. Sequence analysis is applied to call record data from the UK Understanding Society survey. The findings inform further modelling of call record data to increase efficiency in call scheduling.     

Is “Generic Utility Theory” a Suitable Theory of Choice Behavior for Gambles with Mixed Gains and Losses?

Miyamoto's (1988, 1992) generic utility theory (GUT) subsumes a broad class of bilinear utility models. Chechile and Cooke (1997) tested the GUT class of models and found model failure due to the systematic variation of a parameter that should be a positive constant across a range of contexts. In the current study, an improved experimental design is employed to evaluate utility theory. The current study provides further evidence against the GUT class of models for mixed gambles. Moreover, evidence is also provided to demonstrate individual behavior that is incompatible with a coherent bilinear utility theory of choice behavior in the context of mixed gambles with gains and losses.     

Presenting DEA graphically

This paper introduces a methodology that permits presentation of the results of data envelopment analysis (DEA) graphically. A specialized form of multi-dimensional scaling, Co-Plot, enables presentation of the DEA results in a two-dimensional space, hence in a clear, understandable manner. When plotting ratios rather than original data, DEA efficient units can be visualized clearly, as well as their connections to specific variables and/or ratios. Furthermore, Co-Plot can be used in an exploratory data analysis to identify outliers, whose data require additional scrutiny, and potentially inconsequential variables that could be aggregated or removed from the analysis with little effect on the subsequent DEA results.     

Concept mapping internal validity: A case of misconceived mapping?

Since the early 1990s, the concept mapping technique developed by William M. K. Trochim has been widely used by evaluators for program development and evaluation and proven to be an invaluable tool for evaluators and program planners. The technique combines qualitative and statistical analysis and is designed to help identify and prioritize the components, dimensions, and particularities of a given reality. The aim of this paper is to propose an alternative way of conducting the statistical analysis to make the technique even more useful and the results easier to interpret. We posit that some methodological choices made at the inception stage of the technique were ill informed, producing maps of participants’ points-of-view that were not optimal representations of their reality. Such a depiction resulted from the statistical analysis process by which multidimensional scaling (MDS) is being applied on the similarity matrix, followed by a hierarchical cluster analysis (HCA) on the Euclidian distances between statements as plotted on the resulting two-dimensional MDS map. As an alternative, we suggest that HCA should be performed first and MDS second, rather than the reverse. To support this proposal, we present three levels of argument: 1) a logical argument backed up by expert opinions on this issue; 2) statistical evidence of the superiority of our proposed approach and 3) the results of a social validation experiment.     

Multivariate analysis in genstat

Genstat is a general statistical language for data analysis. The facilities for multivariate and cluster analysis within the language are described as well as the many vector and matrix operations which can be used to form multivariate analysis programs. The contents of the standard macro library relevant to multivariate analysis are also discussed.     

基于共词分析的我国低碳政策构成研究

以近22年我国低碳领域的代表性政策为研究对象,运用共词分析法,通过多维尺度分析,可视化地展示了我国低碳政策的政策结构。研究表明:目前我国低碳政策由低碳产业政策、低碳财税政策、低碳投融资政策、碳交易政策、专利政策五大类政策构成。然而,却存在结构性失衡:低碳产业政策与低碳财税政策是现行低碳政策体系的核心,但行政导向性强易致政策失灵;低碳投融资政策与碳交易政策过于薄弱,存在结构性缺失;专利政策的政策中心不明确,存在功能性缺位。由此,提出相应的政策建议。     

Several biplot methods applied to gene expression data

DNA microarray experiments result in enormous amount of data, which need careful interpretation. Biplot approaches show simultaneous display of genes and samples in low-dimensional graphs and thus can be used to represent the relationships between genes and samples. There are several different types of biplots, and these methods need to be evaluated because each plot provides different result.     

Polynomial Primal-Dual Affine Scaling Algorithms in Semidefinite Programming

Two primal-dual affine scaling algorithms for linear programming are extended to semidefinite programming. The algorithms do not require (nearly) centered starting solutions, and can be initiated with any primal-dual feasible solution. The first algorithm is the Dikin-type affine scaling method of Jansen et al. (1993b) and the second the classical affine scaling method of Monteiro et al. (1990). The extension of the former has a worst-case complexity bound of O(₀nL) iterations, where ₀ is a measure of centrality of the the starting solution, and the latter a bound of O(₀nL²) iterations.     

“川江”地名名实变迁与中国历史地名内涵变化规律

在中国历史上,往往出现地名字面本身不变,但所指代的实际范围发生较大变化的现象,这里我们称为“地名内涵变化”,可以简称“地名涵化”。历史上“川江”一词从唐宋之际出现后,其概念的内涵发生了很大的变化。早期宋代“川江”曾有指代整个长江、长江上中下游,指代范围让人相当意外。明清主要指整个长江上游河道,但到近现代,“川江”所指又有一个泛指整个长江上游干支流到仅指乐山到宜昌、宜宾到宜昌、重庆到宜昌河段一个逐步缩小的过程。宋元以前巴蜀地区特殊的政治经济文化地位,使巴蜀航运的地位很高,成为“川江”话语强大指代中下游的支撑。而受长江上游特殊的复杂河道、特殊的平底木船通过性能、特殊地域滩师导航的制约,传统时代长江上游木船运输曾一度在整个长江航运中占有通过性上的优势,一度一定程度上主导着整个长江航运的运行。近代以来“川江”一词的内涵缩小又与机动船进入川江,木船地位相对下降的情形下,热点聚集在机动船运输的话语内有关。研究发现,历史上中国的“地名涵化”可以分成“地名缩放涵化”“地名异地涵化”两种情形,前者较为典型,后者较为复杂。“地名涵化”在时间上又可分成“漫涵化”和“快涵化”两种。一般来说,在历史上行政区划地名的“涵化”较快,而文化区域概念地名“涵化”的过程较为漫长,影响的因素也较为多元,但受国家相关行政区调整的影响,文化区域概念的“地名涵化”过程也会加快。