GPvam-package: Maximum Likelihood Estimation of Multiple Membership Mixed...
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Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling
Description
An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects.
Details
Package: GPvam
Type: Package
Version: 3.0-9
Date: 2023-01-07
License: GPL-2
Author(s)
Andrew Karl, Yan Yang, and Sharon Lohr
Maintainer: Andrew Karl <akarl@asu.edu>
References
Karl, A., Yang, Y. and Lohr, S. (2013) Efficient Maximum Likelihood Estimation of Multiple Membership Linear Mixed Models, with an Application to Educational Value-Added Assessments Computational Statistics & Data Analysis 59, 13–27.
Karl, A., Yang, Y. and Lohr, S. (2014) Computation of Maximum Likelihood Estimates for Multiresponse Generalized Linear Mixed Models with Non-nested, Correlated Random Effects Computational Statistics & Data Analysis 73, 146–162.
Karl, A., Yang, Y. and Lohr, S. (2014) A Correlated Random Effects Model for Nonignorable Missing Data in Value-Added Assessment of Teacher Effects Journal of Educational and Behavioral Statistics 38, 577–603.
Lockwood, J., McCaffrey, D., Mariano, L., Setodji, C. (2007) Bayesian Methods for Scalable Multivariate Value-Added Assesment. Journal of Educational and Behavioral Statistics 32, 125–150.
Mariano, L., McCaffrey, D. and Lockwood, J. (2010) A Model for Teacher Effects From Longitudinal Data Without Assuming Vertical Scaling. Journal of Educational and Behavioral Statistics 35,
253–279.
McCaffrey, D. and Lockwood, J. (2011) Missing Data in Value-Added Modeling of Teavher Effects, Annals of Applied Statistics 5, 773–797
GPvam documentation built on Jan. 8, 2023, 1:10 a.m.
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| GPvam-package | R Documentation |
Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling
Description
An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects.
Details
| Package: | GPvam |
| Type: | Package |
| Version: | 3.0-9 |
| Date: | 2023-01-07 |
| License: | GPL-2 |
Author(s)
Andrew Karl, Yan Yang, and Sharon Lohr
Maintainer: Andrew Karl <akarl@asu.edu>
References
Karl, A., Yang, Y. and Lohr, S. (2013) Efficient Maximum Likelihood Estimation of Multiple Membership Linear Mixed Models, with an Application to Educational Value-Added Assessments Computational Statistics & Data Analysis 59, 13–27.
Karl, A., Yang, Y. and Lohr, S. (2014) Computation of Maximum Likelihood Estimates for Multiresponse Generalized Linear Mixed Models with Non-nested, Correlated Random Effects Computational Statistics & Data Analysis 73, 146–162.
Karl, A., Yang, Y. and Lohr, S. (2014) A Correlated Random Effects Model for Nonignorable Missing Data in Value-Added Assessment of Teacher Effects Journal of Educational and Behavioral Statistics 38, 577–603.
Lockwood, J., McCaffrey, D., Mariano, L., Setodji, C. (2007) Bayesian Methods for Scalable Multivariate Value-Added Assesment. Journal of Educational and Behavioral Statistics 32, 125–150.
Mariano, L., McCaffrey, D. and Lockwood, J. (2010) A Model for Teacher Effects From Longitudinal Data Without Assuming Vertical Scaling. Journal of Educational and Behavioral Statistics 35, 253–279.
McCaffrey, D. and Lockwood, J. (2011) Missing Data in Value-Added Modeling of Teavher Effects, Annals of Applied Statistics 5, 773–797
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