mvglmmRank-package: Multivariate Generalized Linear Mixed Models for Ranking...

In mvglmmRank: Multivariate Generalized Linear Mixed Models for Ranking Sports Teams

Multivariate Generalized Linear Mixed Models for Ranking Sports Teams

Description

Maximum likelihood estimates are obtained via an EM algorithm with either a first-order or a fully exponential Laplace approximation as documented by Broatch and Karl (2018), Karl, Yang, and Lohr (2014), and by Karl (2012). Karl and Zimmerman use this package to illustrate how the home field effect estimator from a mixed model can be biased under nonrandom scheduling.

Details

Package:	mvglmmRank
Type:	Package
Version:	1.2-4
Date:	2023-01-06
License:	GPL-2

See the help pages for mvglmmRank and game.pred

Author(s)

Andrew T. Karl and Jennifer Broatch

Maintainer: Andrew T. Karl <[e-mail]>

References

Broatch, J.E. and Karl, A.T. (2018). Multivariate Generalized Linear Mixed Models for Joint Estimation of Sporting Outcomes. Italian Journal of Applied Statistics. Vol.30, No.2, 189-211. Also available from https://arxiv.org/abs/1710.05284.

Karl, A.T., Zimmerman, D.L. (2021). A Diagnostic for Bias in Linear Mixed Model Estimators Induced by Dependence Between the Random Effects and the Corresponding Model Matrix. Journal of Statistical Planning and Inference, 211, 107-118. https://doi.org/10.1016/j.jspi.2020.06.004.

Karl, A.T., 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 and 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.T. (2012). The Sensitivity of College Football Rankings to Several Modeling Choices, Journal of Quantitative Analysis in Sports, Volume 8, Issue 3, DOI 10.1515/1559-0410.1471

Examples

data(nfl2012)
mvglmmRank(nfl2012,method="PB0",first.order=TRUE,verbose=TRUE,max.iter.EM=1)

result <- mvglmmRank(nfl2012,method="PB0",first.order=TRUE,verbose=TRUE)
print(result)
game.pred(result,home="Denver Broncos",away="Green Bay Packers")

mvglmmRank documentation built on Jan. 8, 2023, 1:12 a.m.