Rasch Measurement Theory Analysis in R (PDF)
(Sprache: Englisch)
Provides researchers & practitioners with a step-by-step guide for conducting Rasch measurement theory analyses. It includes theoretical introductions to major Rasch measurement principles and techniques, demonstrations of analyses using several R packages...
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Provides researchers & practitioners with a step-by-step guide for conducting Rasch measurement theory analyses. It includes theoretical introductions to major Rasch measurement principles and techniques, demonstrations of analyses using several R packages that contain Rasch measurement functions, and sample interpretations of results.
Autoren-Porträt von Stefanie Wind, Cheng Hua
Stefanie A. Wind is an Associate Professor of Educational Measurement at the University of Alabama. Her primary research interests include the exploration of methodological issues in the field of educational measurement, with emphases on methods related to rater-mediated assessments, rating scales, Rasch models, item response theory models, and nonparametric item response theory, as well as applications of these methods to substantive areas related to education.Cheng Hua is a Ph.D. candidate in Educational Measurement program at the University of Alabama. His primary research interests include Rasch Measurement theory, advanced regression models, Bayesian statistics, and visual learning tools (such as Mind Maps and Concept Maps). He enjoys applying his psychometric and statistical skills to address real-world research questions through interdisciplinary collaborations.
Bibliographische Angaben
- Autoren: Stefanie Wind , Cheng Hua
- 2022, 1. Auflage, 322 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1000587711
- ISBN-13: 9781000587715
- Erscheinungsdatum: 07.06.2022
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Größe: 3.97 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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