ERIC Number: EJ901764
Record Type: Journal
Publication Date: 2010-Jun
Pages: 27
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1076-9986
EISSN: N/A
A Model for Teacher Effects from Longitudinal Data without Assuming Vertical Scaling
Mariano, Louis T.; McCaffrey, Daniel F.; Lockwood, J. R.
Journal of Educational and Behavioral Statistics, v35 n3 p253-279 Jun 2010
There is an increasing interest in using longitudinal measures of student achievement to estimate individual teacher effects. Current multivariate models assume each teacher has a single effect on student outcomes that persists undiminished to all future test administrations (complete persistence [CP]) or can diminish with time but remains perfectly correlated (variable persistence [VP]). However, when state assessments do not use a vertical scale or the evolution of the mix of topics present across a sequence of vertically aligned assessments changes as students advance in school, these assumptions of persistence may not be consistent with the achievement data. We develop the "generalized persistence" (GP) model, a Bayesian multivariate model for estimating teacher effects that accommodates longitudinal data that are not vertically scaled by allowing less than perfect correlation of a teacher's effects across test administrations. We illustrate the model using mathematics assessment data. (Contains 3 tables, 3 figures and 6 notes.)
Descriptors: Persistence, Academic Achievement, Data Analysis, Teacher Influence, Longitudinal Studies, Computation, Mathematics Achievement, Scaling, Achievement Tests, Scores, Mathematics Skills, Models, Bayesian Statistics, Elementary Schools
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: Elementary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
IES Funded: Yes
Grant or Contract Numbers: R305U040005