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cvGEE: Cross-Validated Predictions from GEE

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Description

cvGEE calculates cross-validated versions of the logarithmic, quadratic and spherical scoring rules based on generalized estimating equations.

The package presumes that the GEE has been solved using the geeglm() function of the geepack.

Basic Use

We compare a linear and a nonlinear GEE for the dichotomized version of the serum bilirubin biomarker from the PBC dataset:

library("geepack")
library("cvGEE")
library("splines")
library("lattice")

pbc2$serBilirD <- as.numeric(pbc2$serBilir > 1.2)

gm1 <- geeglm(serBilirD ~ year * drug, 
              family = binomial(), data = pbc2, id = id, 
              corstr = "exchangeable")

gm2 <- geeglm(serBilirD ~ ns(year, 3, Boundary.knots = c(0, 10)) * drug, 
              family = binomial(), data = pbc2, id = id, 
              corstr = "exchangeable")

plot_data <- cv_gee(gm1, return_data = TRUE)
plot_data$linear <- plot_data$.score
plot_data$non_linear <- unlist(cv_gee(gm2))

xyplot(linear + non_linear ~ year | .rule, data = plot_data, 
       type = "smooth", auto.key = TRUE, layout = c(3, 1),
       scales = list(y = list(relation = "free")),
       xlab = "Follow-up time (years)", ylab = "Scoring Rules")

Installation

The development version of the package can be installed from GitHub using the devtools package:

devtools::install_github("drizopoulos/cvGEE")

and with vignettes

devtools::install_github("drizopoulos/cvGEE", build_vignettes = TRUE)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.