Semi‐automated Rasch analysis using in‐plus‐out‐of‐questionnaire log likelihood.
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| Title: | Semi‐automated Rasch analysis using in‐plus‐out‐of‐questionnaire log likelihood. |
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| Authors: | Wijayanto, Feri (AUTHOR), Mul, Karlien (AUTHOR), Groot, Perry (AUTHOR), van Engelen, Baziel G.M. (AUTHOR), Heskes, Tom (AUTHOR) |
| Source: | British Journal of Mathematical & Statistical Psychology. May2021, Vol. 74 Issue 2, p313-339. 27p. |
| Subjects: | Procedure manuals, Integrated software, Rasch models |
| Abstract: | Rasch analysis is a popular statistical tool for developing and validating instruments that aim to measure human performance, attitudes and perceptions. Despite the availability of various software packages, constructing a good instrument based on Rasch analysis is still considered to be a complex, labour‐intensive task, requiring human expertise and rather subjective judgements along the way. In this paper we propose a semi‐automated method for Rasch analysis based on first principles that reduces the need for human input. To this end, we introduce a novel criterion, called in‐plus‐out‐of‐questionnaire log likelihood (IPOQ‐LL). On artificial data sets, we confirm that optimization of IPOQ‐LL leads to the desired behaviour in the case of multi‐dimensional and inhomogeneous surveys. On three publicly available real‐world data sets, our method leads to instruments that are, for all practical purposes, indistinguishable from those obtained by Rasch analysis experts through a manual procedure. [ABSTRACT FROM AUTHOR] |
| Copyright of British Journal of Mathematical & Statistical Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Rasch analysis is a popular statistical tool for developing and validating instruments that aim to measure human performance, attitudes and perceptions. Despite the availability of various software packages, constructing a good instrument based on Rasch analysis is still considered to be a complex, labour‐intensive task, requiring human expertise and rather subjective judgements along the way. In this paper we propose a semi‐automated method for Rasch analysis based on first principles that reduces the need for human input. To this end, we introduce a novel criterion, called in‐plus‐out‐of‐questionnaire log likelihood (IPOQ‐LL). On artificial data sets, we confirm that optimization of IPOQ‐LL leads to the desired behaviour in the case of multi‐dimensional and inhomogeneous surveys. On three publicly available real‐world data sets, our method leads to instruments that are, for all practical purposes, indistinguishable from those obtained by Rasch analysis experts through a manual procedure. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00071102 |
| DOI: | 10.1111/bmsp.12218 |
