Waugh Russell F, Chapman Elaine S
Graduate School of Education, The University of Western Australia, Stirling Highway, Nedlands, WA, 6009, Australia.
J Appl Meas. 2005;6(1):80-99.
One often hears the question asked, "For questionnaire data measuring a variable, what difference does it make to use factor analysis/principal components analysis (true-score theory) or Rasch measurement in testing for dimensionality?" This paper reports both factor analysis and Rasch measurement analysis for two sets of data. One set of data measures social anxiety for primary school students (N=436, I=10) and the second measures attitude to mathematics for primary-aged students (N=774, I=10). For both sets of data, the factor analysis suggests that the scores are reliable, and that inferences can be made that are valid for measuring school anxiety and attitude to mathematics. For both sets of data analyzed with Rasch measurement techniques, the reliability of the measures, the dimensionality of the measures, and the initial conceptualisation of the items, are called into question. It suggests that one cannot make valid inferences from the measures that were initially set up for true-score theory. The Rasch analysis suggests that items intended to measure a variable should be initially developed on a conceptualized scale from easy to hard, and that students should answer the items from this perspective, so that the Rasch analysis of the data tests this conceptualisation, and a linear scale can be created based on a mathematical measurement model with consistent units (logits).
“对于测量某一变量的问卷数据，在进行维度检验时，使用因子分析/主成分分析（真分数理论）或拉施测量会有什么不同？”本文报告了对两组数据进行的因子分析和拉施测量分析。一组数据测量小学生的社交焦虑（N = 436，I = 10），另一组测量小学年龄段学生对数学的态度（N = 774，I = 10）。对于这两组数据，因子分析表明分数是可靠的，并且可以做出对测量学校焦虑和对数学的态度有效的推断。对于用拉施测量技术分析的两组数据，测量的可靠性、测量的维度以及项目的初始概念化都受到了质疑。这表明，从最初为真分数理论设立的测量中无法做出有效的推断。拉施分析表明，旨在测量某一变量的项目最初应在从易到难的概念化量表上开发，并且学生应从这个角度回答项目，以便对数据进行拉施分析来检验这种概念化，并且可以基于具有一致单位（对数单位）的数学测量模型创建线性量表。
