Assumptions of Value-Added Models for Estimating School Effects

By Sean F. Reardon, Stephen Raudenbush. Education Finance and Policy, 2009

138 citations recorded by the source corpus.

Subfields: Education, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7a61dc4a10bd0c6f12684a4275509dda4ca6ce45

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Education

1. Matthew Ronfeldt
2. Julie Cohen
3. Pam Grossman
4. J. Soland
5. L. Major
6. Cesare Aloisi
7. Lindsay Fox
8. Steven I. Higgins

In Statistics and Probability

1. L. Major
2. Cesare Aloisi
3. Steven I. Higgins
4. R. Coe
5. K. R. Mahan

Citations in the corpus

• The Test Matters (2014, background): “…their differentiating potential, there have been numerous critiques of VAMs, including the assumptions underlying them, their measurement properties, and their stability over time (Hill, 2009; Koretz, 2008; McCaffrey, Sass, Lockwood, & Mihaly, 2009; Reardon & Raudenbush, 2009; Rothstein, 2009).”
• Is a Good Teacher a Good Teacher for All? Comparing Value-Added of Teachers With Their English Learners and Non-English Learners (2014, background): “Despite the prevalence of VAM, value-added research often relies on a fundamental yet untested assumption that a teacher who is effective for one student is effective for other students with different needs (Reardon & Raudenbush, 2009).”
• What Makes Great Teaching? Review of the Underpinning Research. (2014, background): “Reardon and Raudenbush (2009) set out to examine the assumptions required to interpret value-added estimates of learning gain as a causal effect of teaching.”