人气
项目反应理论
计算机科学
集合(抽象数据类型)
背景(考古学)
比例(比率)
数据集
样品(材料)
数据科学
考试(生物学)
数据挖掘
计量经济学
统计
心理学
人工智能
心理测量学
数学
社会心理学
地理
地图学
古生物学
化学
考古
生物
程序设计语言
色谱法
作者
Klaas Sijtsma,L. Andries van der Ark
摘要
Over the past decade, Mokken scale analysis ( MSA ) has rapidly grown in popularity among researchers from many different research areas. This tutorial provides researchers with a set of techniques and a procedure for their application, such that the construction of scales that have superior measurement properties is further optimized, taking full advantage of the properties of MSA . First, we define the conceptual context of MSA , discuss the two item response theory ( IRT ) models that constitute the basis of MSA , and discuss how these models differ from other IRT models. Second, we discuss dos and don'ts for MSA ; the don'ts include misunderstandings we have frequently encountered with researchers in our three decades of experience with real‐data MSA . Third, we discuss a methodology for MSA on real data that consist of a sample of persons who have provided scores on a set of items that, depending on the composition of the item set, constitute the basis for one or more scales, and we use the methodology to analyse an example real‐data set.
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