score_fun_gee: score_fun_gee

In JakubStats/marge: Multivariate Adaptive Regression splines using Generalized estimating Equations

score_fun_gee

Description

Given estimates from the null and the design matrix from alternative model, find the score statistic (this is used for GEEs only).

Usage

score_fun_gee(
  Y,
  N,
  n_vec,
  VS.est_list,
  AWA.est_list,
  J2_list,
  Sigma2_list,
  J11.inv,
  JSigma11,
  mu.est,
  V.est,
  B1,
  XA,
  nb = FALSE,
  ...
)

Arguments

Y	: the response variable.
N	: the number of clusters.
n_vec	: a vector consisting of the cluster sizes for each cluster.
VS.est_list	: a product of matrices.
AWA.est_list	: a product of matrices.
J2_list	: a product of matrices.
Sigma2_list	: a product of matrices.
J11.inv	: a product of matrices.
JSigma11	: a product of matrices.
mu.est	: estimates of the fitted mean under the null model.
V.est	: estimates of the fitted variance under the null model.
B1	: model matrix under the null model.
XA	: model matrix under the alternative model.
nb	: a logical argument, is the model a negative binomial model? The default is FALSE.
...	: further arguments passed to or from other methods.

Value

score_fun_gee returns a calculated score statistic for the null and alternative model when fitting a GEE.

Author(s)

Jakub Stoklosa and David I. Warton

References

Stoklosa, J., Gibb, H. and Warton, D.I. (2014). Fast forward selection for generalized estimating equations with a large number of predictor variables. Biometrics, 70, 110–120.

Stoklosa, J. and Warton, D.I. (2018). A generalized estimating equation approach to multivariate adaptive regression splines. Journal of Computational and Graphical Statistics, 27, 245–253.

See Also

score_fun_glm

JakubStats/marge documentation built on Feb. 25, 2024, 9:38 p.m.