Causal Inference for Time-Varying Instructional Treatments

Autor/inn/en	Hong, Guanglei; Raudenbush, Stephen W.
Titel	Causal Inference for Time-Varying Instructional Treatments
Quelle	In: Journal of Educational and Behavioral Statistics, 33 (2008) 3, S.333-362 (30 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998607307355
Schlagwörter	Elementary School Mathematics; Grade 4; Probability; Teaching Methods; Inferences; Causal Models; Grade 5; Mathematics Instruction; Time Factors (Learning); Observation; Elementary School Students; Student Placement; Teaching Skills; Teacher Influence; Peer Influence; Computation; Longitudinal Studies; Mathematics Achievement; Educational Environment; Environmental Influences; Educational Methods + Suchen Sie Ihr Suchwort? Elementare Mathematik; Schulmathematik; School year 04; 4. Schuljahr; Schuljahr 04; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Teaching method; Lehrmethode; Unterrichtsmethode; Inference; Inferenz; Kausalanalyse; School year 05; 5. Schuljahr; Schuljahr 05; Mathematics lessons; Mathematikunterricht; Beobachtung; Schülerpraktikum; Lehrbefähigung; Lehrkompetenz; Unterrichtsbefähigung; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Lernumgebung; Pädagogische Umwelt; Schulumwelt; Environmental influence; Umwelteinfluss; Educational method; Erziehungsmethode
Abstract	The authors propose a strategy for studying the effects of time-varying instructional treatments on repeatedly observed student achievement. This approach responds to three challenges: (a) The yearly reallocation of students to classrooms and teachers creates a complex structure of dependence among responses; (b) a child's learning outcome under a certain treatment may depend on the treatment assignment of other children, the skill of the teacher, and the classmates and teachers encountered in the past years; and (c) time-varying confounding poses special problems of endogeneity. The authors address these challenges by modifying the stable unit treatment value assumption to identify potential outcomes and causal effects and by integrating inverse probability of treatment weighting into a four-way value-added hierarchical model with pseudolikelihood estimation. Using data from the Longitudinal Analysis of School Change and Performance, the authors apply these methods to study the impact of "intensive math instruction" in Grades 4 and 5. (Contains 4 tables and 1 figure.) (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10