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IES Grant

Title: Enhanced Value-Added Models for Estimating Teacher Effects
Center: NCER Year: 2004
Principal Investigator: Lockwood, J. R. Awardee: RAND Corporation
Program: Statistical and Research Methodology in Education      [Program Details]
Award Period: 3 years Award Amount: $500,000
Type: Methodological Innovation Award Number: R305U040005
Description:

This research will examine the performance of a class of value-added models for longitudinal student achievement data where we introduce and use latent student parameters to enrich other features of the model. The two primary model enrichments are (1) allowing teacher effects to depend on the latent student parameters, and (2) allowing the probability of students missing testing to depend on the latent student parameters.

Email J.R. Lockwood for additional information: lockwood@rand.org.

Publications

Journal article, monograph, or newsletter

Lockwood, J.R., and McCaffrey, D.F. (2007). Controlling for Individual Heterogeneity in Longitudinal Models, With Applications to Student Achievement. Electronic Journal of Statistics, 1, 223–252.

Lockwood, J.R., and McCaffrey, D.F. (2009). Exploring Student-Teacher Interactions in Longitudinal Achievement Data. Education Finance and Policy, 4(4), 439–467.

Lockwood, J.R., Mccaffrey, D.F., Hamilton, L.S., Stecher, B., Le, V., and Martinez, J. (2007). The Sensitivity of Value-Added Teacher Effect Estimates to Different Mathematics Achievement Measures. Journal of Educational Measurement, 44(1): 47–67.

Lockwood, J.R., Mccaffrey, D.F., Mariano, L.T., and Setodji, C. (2007). Bayesian Methods for Scalable Multivariate Value-Added Assessment. Journal of Educational and Behavioral Statistics, 32(2): 125–150.

Mariano, L.T., Mccaffrey, D.F., and Lockwood, J.R. (2010). A Model for Teacher Effects From Longitudinal Data Without Assuming Vertical Scaling. Journal of Educational and Behavioral Statistics, 35(3): 253–279.

McCaffrey, D.F., and Lockwood, J.R. (2011). Missing Data in Value-Added Modeling of Teacher Effects. The Annals of Applied Statistics, 773–797.

** This project was submitted to and funded as an Unsolicited application in FY 2006.


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