plotGAMM: GAMM plotting using ggplot2

In neuroconductor/voxel: Mass-Univariate Voxelwise Analysis of Medical Imaging Data

Description

GAMM plotting using ggplot2

Usage

plotGAMM(gammFit, smooth.cov, groupCovs = NULL, orderedAsFactor = F,
  rawOrFitted = F, plotCI = T, grouping = NULL)

Arguments

gammFit	fitted gam model as produced by gamm4::gamm()
smooth.cov	(character) name of smooth term to be plotted
groupCovs	(character) name of group variable to plot by, if NULL (default) then there are no groups in plot
orderedAsFactor	Disabled
rawOrFitted	If FALSE (default) then only smooth terms are plotted; if rawOrFitted = "raw" then raw values are plotted against smooth; if rawOrFitted = "fitted" then fitted values are plotted against smooth
plotCI	if TRUE (default) upper and lower confidence intervals are added at 2 standard errors above and below the mean
grouping	(character) Name of variable that you want to use as the group argument in ggplot2::aes(), useful for better visualization of longitudinal data, (default is NULL)

Value

Returns a ggplot object that can be visualized using the print() function

See Also

Other Plotting: plotGAM

Examples

set.seed(1)
data <- data.frame(x = (seq(.25,25, .25) +rnorm(100)), group = rep(1:2, 5), z=rnorm(100),
              index.rnorm = rep(rnorm(50, sd = 50), 2), index.var = rep(1:50, 2))
data$y <- (data$x)*data$group*10 + rnorm(100, sd = 700) + data$index.rnorm + data$z
data$group <- ordered(data$group)


gamm <- gamm4::gamm4(y ~ + s(x) + s(x, by=group) + z + group, data=data, random = ~ (1|index.var))


plot <- plotGAMM(gammFit <- gamm, smooth.cov <- "x", groupCovs = "group",
                    plotCI <- T, rawOrFitted = "raw", grouping = "index.var")

plot2 <- plotGAMM(gammFit <- gamm, smooth.cov <- "x", groupCovs = "group",
                  plotCI <- T, rawOrFitted = "fitted", grouping = "index.var")

neuroconductor/voxel documentation built on May 20, 2021, 9:39 p.m.