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Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables (Journal Article)

Author

Listed:
  • Matthew T. Johnson
  • Stephen Lipscomb
  • Brian Gill

Abstract

Teacher value-added models (VAMs) must isolate teachers’ contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model.

Suggested Citation

  • Matthew T. Johnson & Stephen Lipscomb & Brian Gill, 2015. "Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables (Journal Article)," Mathematica Policy Research Reports 4a9776a57ae9477e80df47e7d, Mathematica Policy Research.
    • Handle: RePEc:mpr:mprres:4a9776a57ae9477e80df47e7d9319a25
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    File URL: http://www.tandfonline.com/doi/full/10.1080/19345747.2014.967898#.VLkQFHYo7q4
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    Citations

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    Cited by:

    1. J. R. Lockwood & Daniel F. McCaffrey, 2019. "Impact Evaluation Using Analysis of Covariance With Error-Prone Covariates That Violate Surrogacy," Evaluation Review, , vol. 43(6), pages 335-369, December.
    2. J. R. Lockwood & D. McCaffrey, 2020. "Using hidden information and performance level boundaries to study student–teacher assignments: implications for estimating teacher causal effects," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1333-1362, October.
    3. Eric Parsons & Cory Koedel & Li Tan, 2019. "Accounting for Student Disadvantage in Value-Added Models," Journal of Educational and Behavioral Statistics, , vol. 44(2), pages 144-179, April.
    4. Jonah Deutsch & Matthew Johnson & Brian Gill, "undated". "The Promotion Power Impacts of Louisiana High Schools," Mathematica Policy Research Reports 2c041387caf14e9eac49cd539, Mathematica Policy Research.
    5. Elias Walsh & Dallas Dotter & Albert Y. Liu, "undated". "Can More Teachers Be Covered? The Accuracy, Credibility, and Precision of Value-Added Estimates with Proxy Pre-Tests," Mathematica Policy Research Reports c61e6b4de71b4741b12bc978d, Mathematica Policy Research.
    6. Julie Bruch & Jonathan Gellar & Lindsay Cattell & John Hotchkiss & Phil Killewald, "undated". "Using Data from Schools and Child Welfare Agencies to Predict Near-Term Academic Risks, Appendixes," Mathematica Policy Research Reports 1386d532a9684dda96c3589da, Mathematica Policy Research.
    7. Horoi, Irina & Ost, Ben, 2015. "Disruptive peers and the estimation of teacher value added," Economics of Education Review, Elsevier, vol. 49(C), pages 180-192.
    8. Julie Bruch & Jonathan Gellar & Lindsay Cattell & John Hotchkiss & Phil Killewald, "undated". "Using Data from Schools and Child Welfare Agencies to Predict Near-Term Academic Risks," Mathematica Policy Research Reports 2c2de769f8e44b728e9be5a90, Mathematica Policy Research.

    More about this item

    Keywords

    Value-added models ; teacher evaluation ; education;
    All these keywords.

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