Generating Hypotheses and Upper-Bound Effect Sizes Using a Large Number of School Characteristics and Student Outcomes

Autor/in	Long, Mark C.
Titel	Generating Hypotheses and Upper-Bound Effect Sizes Using a Large Number of School Characteristics and Student Outcomes
Quelle	In: Journal of Research on Educational Effectiveness, 9 (2016) 1, S.128-147 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1934-5747
DOI	10.1080/19345747.2015.1070939
Schlagwörter	Hypothesis Testing; Effect Size; High School Students; Student Characteristics; Outcomes of Education; Academic Achievement; Statistical Analysis; Input Output Analysis; Sample Size; Robustness (Statistics); Error of Measurement; Educational Research; Hierarchical Linear Modeling; Longitudinal Studies; Grade 8; Grade 10; Grade 12 + Suchen Sie Ihr Suchwort? Hypothesenprüfung; Hypothesentest; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Lernleistung; Schulerfolg; Schulleistung; Statistische Analyse; Widerstandsfähigkeit; Messfehler; Bildungsforschung; Pädagogische Forschung; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; School year 08; 8. Schuljahr; Schuljahr 08; School year 12; 12. Schuljahr; Schuljahr 12
Abstract	Using a "naïve" specification, this paper estimates the relationship between 36 high school characteristics and 24 student outcomes controlling for students' pre-high school characteristics. The goal of this exploration is not to generate casual estimates, but rather to: (a) compare the size of the relationships to determine which inputs seem most promising and to identify which student outcomes appear most susceptible to being affected; (b) obtain likely upper-bound effect sizes that are useful information for power analyses used to establish minimum sample sizes for more robust designs capable of revealing causal impacts; and (c) illustrate how small effects over many outcomes (which are cumulatively important) can be easily missed. I find that most of the 36 inputs appear to have affected more outcomes than one would expect by chance, but that the apparent effects were generally small. Further, I find a higher frequency of large and significant apparent effects on educational achievement and attainment outcomes than labor market and other outcomes for young adults. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01