I want to create a sjPlot
-ish coefficient plot using dwplot()
because my model outputs (odds-ratio-lized logit coefs and s.e.) cannot be directly fed into the former. I want the output to display coef > 1 in "#377EB8" and those <= 1 in "#E41A1C" along both sides of the vertical reference line = 1 using sjPlot
's default Set1
color palette.
However, I found it difficult to trick R
to do what I want, below is my current code:
# load the data
mydf <- readRDS(url("https://www.dropbox.com/s/m6o3aohbu2iwge2/mydf.rds?dl=1"))
library(ggplot2)
library(dotwhisker)
p <- dwplot(df, vline = ggplot2::geom_vline(xintercept = 1,
colour = "grey90",
linetype = 1,
size = 1))
theme_classic()
theme(legend.position="none", plot.title = element_text(hjust = 0.5, face="bold"))
xlab("Odds ratio")
p scale_fill_manual(values=c("#E41A1C", "#377EB8"))
geom_segment(aes(x=conf.low,y=term,xend=conf.high,
yend=term,col=estimate > 1))
geom_point(aes(x=estimate,y=term,col=estimate > 1))
But the colors of the output look strange, don't look quite like the exact color scheme shown in
CodePudding user response:
The issue is that you use scale_fill_manual
but map on the color
aes, i.e. use scale_color_manual
. Additionally under the hood there is already something mapped on the color
which results in an error
Insufficient values in manual scale. 3 needed but only 2 provided.
This could be fixed by using a named color vector (or by setting the limits) which also ensures that the right colors are assigned to the categories.
library(ggplot2)
library(dotwhisker)
p <- dwplot(mydf, vline = ggplot2::geom_vline(
xintercept = 1,
colour = "grey90",
linetype = 1,
size = 1
))
theme_classic()
theme(legend.position = "none", plot.title = element_text(hjust = 0.5, face = "bold"))
xlab("Odds ratio")
p
scale_color_manual(values = c("FALSE" = "#E41A1C", "TRUE" = "#377EB8"))
geom_segment(aes(
x = conf.low, y = term, xend = conf.high,
yend = term, col = estimate > 1
))
geom_point(aes(x = estimate, y = term, col = estimate > 1))
DATA
structure(list(term = structure(1:5, names = c("X1", "X2", "X3",
"X4", "X5"), levels = c("X1", "X2", "X3", "X4", "X5"), class = "factor"),
estimate = c(0.990945229592862, 1.01649975436596, 0.981822272245729,
1.00200300047509, 1.11234308470697), conf.low = c(0.978268803948375,
1.0054731859839, 0.970707803486251, 0.993648103170243, 1.10200032988942
), conf.high = c(1.00118816776943, 1.02503427463924, 0.993972524876506,
1.01282670058945, 1.12476153238761), sign = c("#377EB8",
"#E41A1C", "#377EB8", "#E41A1C", "#E41A1C")), row.names = c("X1",
"X2", "X3", "X4", "X5"), class = "data.frame")