autoplot.Wald_lmm | R Documentation |
Graphical Display For Linear Hypothesis Test
## S3 method for class 'Wald_lmm'
autoplot(object, type = "forest", size.text = 16, add.args = NULL, ...)
## S3 method for class 'Wald_lmm'
plot(x, ...)
object, x |
a |
type |
[character] what to display: a forest plot ( |
size.text |
[numeric, >0] size of the font used to display text. |
add.args |
[list] additional arguments used to customized the graphical display. Must be a named list. See details. |
... |
arguments passed to the confint method. |
Argument add.args: parameters specific to the forest plot:
color
: [logical] should the estimates be colored by global null hypothesis, e.g. when testing the effect of a 3 factor covariate, the two corresponding coefficient will have the same color. Alternatively a vector of positive integers giving the color with which each estimator should be displayed.
color
: [logical] should the estimates be represented by a different shape per global null hypothesis, e.g. when testing the effect of a 3 factor covariate, the two corresponding coefficient will have the same type of point. Alternatively a vector of positive integers describing the shape to be used for each estimator.
ci
: [logical] should confidence intervals be displayed?
size.estimate
: [numeric, >0] size of the dot used to display the estimates.
size.ci
: [numeric, >0] thickness of the line used to display the confidence intervals.
width.ci
: [numeric, >0] width of the line used to display the confidence intervals.
size.null
: [numeric, >0] thickness of the line used to display the null hypothesis.
Parameters specific to the heatmap plot:
limits
: [numeric vector of length 2] minimum and maximum value of the colorscale relative to the correlation.
low
, mid
, high
: [character] color for the the colorscale relative to the correlation.
midpoint
: [numeric] correlation value associated with the color defined by argument mid
A list with two elements
data
: data used to create the graphical display.
plot
: ggplot object.
plot(Wald_lmm)
: Graphical Display For Linear Hypothesis Test
## From the multcomp package
if(require(datasets) && require(ggplot2)){
## only tests with 1 df
ff <- Fertility ~ Agriculture + Examination + Education + Catholic + Infant.Mortality
e.lmm <- lmm(ff, data = swiss)
e.aovlmm <- anova(e.lmm)
autoplot(e.aovlmm, type = "forest")
autoplot(e.aovlmm, type = "heat") ## 3 color gradient
autoplot(e.aovlmm, type = "heat", add.args = list(mid = NULL)) ## 2 color gradient
## test with more than 1 df
e.lmm2 <- lmm(breaks ~ tension + wool, data = warpbreaks)
e.aovlmm2 <- anova(e.lmm2)
autoplot(e.aovlmm2)
autoplot(e.aovlmm2, add.args = list(color = FALSE, shape = FALSE))
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.