To Aggregate or Not and Potentially Better Questions for Clustered Data: The Need for Hierarchical Linear Modeling in CTE Research

Autor/in	Nimon, Kim
Titel	To Aggregate or Not and Potentially Better Questions for Clustered Data: The Need for Hierarchical Linear Modeling in CTE Research
Quelle	In: Career and Technical Education Research, 37 (2012) 3, S.213-233 (21 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1554-7558
DOI	10.5328/cter37.3.213
Schlagwörter	Vocational Education; Educational Research; Hierarchical Linear Modeling; Multivariate Analysis; Context Effect; Research Methodology; Grade 11; Scores; Urban Schools; Science Instruction; Texas + Suchen Sie Ihr Suchwort? Ausbildung; Berufsbildung; Bildungsforschung; Pädagogische Forschung; Multivariate Analyse; Research method; Forschungsmethode; School year 11; 11. Schuljahr; Schuljahr 11; Urban area; Urban areas; School; Schools; Stadtregion; Stadt; Schule; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht
Abstract	Using state achievement data that are openly accessible, this paper demonstrates the application of hierarchical linear modeling within the context of career technical education research. Three prominent approaches to analyzing clustered data (i.e., modeling aggregated data, modeling disaggregated data, modeling hierarchical data) are discussed and demonstrated. Syntax to replicate the analyses are included which may help break the learning curve associated with conducting and interpreting the results of this advanced statistical technique. (Contains 5 tables, 1 figure and 1 note.) (As Provided).
Anmerkungen	Association for Career and Technical Education Research. Web site: http://www.public.iastate.edu/~laanan/actermain/publications.shtml
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10