plot: Plot method for GPvam

In GPvam: Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling

Plot method for GPvam

Description

Plot teacher effects and residuals. The caterpillar plots use a modified version of the plotCI function from R package gplots. According to that package, "Original version [of plotCI] by Bill Venables [e-mail] posted to r-help on Sep. 20, 1997. Enhanced version posted to r-help by Ben Bolker [e-mail] on Apr. 16, 2001. This version was modified and extended by Gregory R. Warnes [e-mail]. Additional changes suggested by Martin Maechler [e-mail] integrated on July 29, 2004."

Usage

## S3 method for class 'GPvam'
plot(x, ..., alpha)

Arguments

x	an object of class GPvam
...	other arguments
alpha	the significance level for the caterpillar plots

Value

Requires user to click window or press "enter" to progress through plots. Returns caterpillar plots (via the package gplots) and residual plots.

Author(s)

Andrew Karl [e-mail] Yan Yang Sharon Lohr

Other authors as listed above for the caterpillar plots.

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

See Also

summary.GPvam

Examples

data(vam_data)

GPvam(vam_data,student.side="R",persistence="VP",
fixed_effects=formula(~as.factor(year)+cont_var+0),verbose=TRUE,max.iter.EM=1)

result <- GPvam(vam_data,student.side="R",persistence="VP",
fixed_effects=formula(~as.factor(year)+cont_var+0),verbose=TRUE)
 summary(result)

 plot(result)
                

GPvam documentation built on Jan. 8, 2023, 1:10 a.m.