Knowledge space theory, formal concept analysis, and computerized psychological assessment

计算机科学 形式概念分析 重新解读 一般化 背景(考古学) 集合(抽象数据类型) 构造(python库) 代表(政治) 可靠性(半导体) 空格(标点符号) 独立性(概率论) 人工智能 数学 算法 统计 法学 程序设计语言 物理 功率(物理) 古生物学 数学分析 操作系统 政治 生物 量子力学 声学 政治学
作者
Andrea Spoto,Luca Stefanutti,Giulio Vidotto
出处
期刊:Behavior Research Methods [Springer Science+Business Media]
卷期号:42 (1): 342-350 被引量:36
标识
DOI:10.3758/brm.42.1.342
摘要

In the present study, the use of knowledge space theory (KST), jointly with formal concept analysis (FCA), is proposed for developing a formal representation of the relations between the items of a questionnaire and a set of psychodiagnostic criteria. This formal representation can be used to develop an efficient adaptive tool for psychological assessment. Rusch and Wille (1996) have shown some interesting connections between KST and FCA; these connections are applied in the construction of knowledge structures, starting from a formal context representing the relations between items and criteria. The proposed general methodology was applied, as an example, to the Maudsley Obsessional-Compulsive Questionnaire. We used a data set provided by a sample of patients with a diagnosis of obsessive-compulsive disorder to validate the obtained structures. The parameters of the basic local independence model (BLIM) were estimated for the obtained knowledge structures. The fit of each model was tested by parametric bootstrap because of the sparseness of the derived data matrix. The results are discussed in light of both psychological and methodological relapses. In particular, we propose a reinterpretation of the BLIM parameters that seems suitable for testing reliability and construct validity; furthermore, it is pointed out how the obtained structures could represent the starting point for the development of a computerized assessment tool.
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