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A tutorial on how to do a Mokken scale analysis on your test and questionnaire data
Author(s) -
Sijtsma Klaas,
Ark L. Andries
Publication year - 2017
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/bmsp.12078
Subject(s) - popularity , item response theory , computer science , set (abstract data type) , context (archaeology) , scale (ratio) , data set , sample (material) , data science , test (biology) , data mining , econometrics , statistics , psychology , artificial intelligence , psychometrics , mathematics , social psychology , geography , cartography , paleontology , chemistry , archaeology , biology , programming language , chromatography
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.