voxel (version 1.3.5)

plotGAMM: GAMM plotting using ggplot2

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

# NOT RUN {
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")
# }