Péladeau Normand, Dagenais Christian, Ridde Valéry
Provalis Research, 1255 Robert Bourassa Blvd Suite 1604, Montréal, QC H3B 3X3, Canada.
Department of Psychology, University of Montreal, Pavillon Marie-Victorin, Room C355, P.O. Box 6128, Centre-ville Station, Montreal, Quebec, H3C 3J7, Canada.
Eval Program Plann. 2017 Jun;62:56-63. doi: 10.1016/j.evalprogplan.2017.02.005. Epub 2017 Feb 11.
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.
自20世纪90年代初以来,威廉·M·K·特罗奇姆开发的概念映射技术已被评估人员广泛用于项目开发和评估,并被证明是评估人员和项目规划者的宝贵工具。该技术将定性分析和统计分析相结合,旨在帮助识别给定现实的组成部分、维度和特殊性,并确定其优先级。本文的目的是提出一种进行统计分析的替代方法,以使该技术更有用,结果更易于解释。我们认为,该技术在初始阶段做出的一些方法选择缺乏充分依据,导致生成的参与者观点地图并非其现实的最佳呈现。这种描绘源于统计分析过程,即在相似性矩阵上应用多维尺度分析(MDS),然后对在所得二维MDS地图上绘制的陈述之间的欧几里得距离进行层次聚类分析(HCA)。作为替代方案,我们建议应先进行HCA,再进行MDS,而不是相反的顺序。为支持这一建议,我们提出了三个层面的论据:1)基于该问题专家意见的逻辑论据;2)我们提出的方法优越性的统计证据;3)社会验证实验的结果。