Abstract
Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles. By accounting for response styles, it provides a simple remedy for the bias that occurs if the response style is ignored. The model allows to include explanatory variables that have a content-related effect as well as an effect on the response style. A visualization tool is developed that makes the interpretation of effects easily accessible. The proposed model is embedded into the framework of multivariate generalized linear model, which entails that common estimation and inference tools can be used. Existing software can be used to fit the model, which makes it easy to apply.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Mathematik, Informatik und Statistik > Statistik |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
URN: | urn:nbn:de:bvb:19-epub-47465-8 |
ISSN: | 1076-9986 |
Allianz-/Nationallizenz: | Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich. |
Sprache: | Englisch |
Dokumenten ID: | 47465 |
Datum der Veröffentlichung auf Open Access LMU: | 27. Apr. 2018, 08:13 |
Letzte Änderungen: | 04. Nov. 2020, 13:24 |