Reference : Comparing regression approaches in modelling (non-)compensatory judgement formation

	Document type :	Parts of books : Contribution to collective works
	Discipline(s) :	Social & behavioral sciences, psychology : Sociology & social sciences Social & behavioral sciences, psychology : Social, industrial & organizational psychology Social & behavioral sciences, psychology : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/10993/8193

Title :	Comparing regression approaches in modelling (non-)compensatory judgement formation
Language :	English
Author, co-author :	Hörstermann, Thomas [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Languages, Culture, Media and Identities (LCMI) >]
	Krolak-Schwerdt, Sabine [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Languages, Culture, Media and Identities (LCMI) >]
Publication date :	In press
Main document title :	Studies in classification, data analysis and knowledge organization
Publisher :	Springer
Collection and collection volume :	Vol. 45: Data Analysis, Machine Learning and Knowledge Discovery
Peer reviewed :	Yes
City :	Berlin
Country :	Germany
Abstract :	[en] Applied research on judgment formation, e.g. in education, is interested in identifying the underlying judgment rules from empirical judgment data. Psychological theories and empirical results on human judgment formation support the assumption of compensatory strategies, e.g. (weighted) linear models, as well as non compensatory (heuristic) strategies as underlying judgment rules. Previous research repeatedly demonstrated that linear regression models well fitted empirical judgment data, leading to the conclusion that the underlying cognitive judgment rules were also linear and compensatory. This simulation study investigated whether a good fit of a linear regression model is a valid indicator of a compensatory cognitive judgment formation process. Simulated judgment data sets with underlying compensatory and noncompensatory judgment rules were generated to reflect typical judgment data from applied educational research. Results indicated that linear regression models well fitted even judgment data with underlying non compensatory judgment rules, thus impairing the validity of the fit of the linear model as an indicator of compensatory cognitive judgment processes.
Permalink :	http://hdl.handle.net/10993/8193

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	Fulltext file(s): File Commentary Version Size Access Limited access Hörstermann-Krolak-in press-preprint-Comparison of regression-final.pdf This article does not exactly replicate the final version published in the journal [Journal of Media Psychology]. It is not a copy of the original published article and is not suitable for citation. Author preprint 78.59 kB Request a copy

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