dat2<-read.delim("clipboard")#Copiar los datos en el portapapeles
dat$IDN=as.factor(dat$IDN)
attach(dat2)
m11 <- geeglm(
formula = log(Timmo)~ presa+picaduras,
data = dat2,
id = IDN,
corstr = "exchangeable"
)
plot_model(m11, type = "pred", terms = c("picaduras", "presa"))
When plotting the data I get this error: # Model has log-transformed response. Back-transforming predictions to original response scale. Standard errors are still on the log-scale
My question is, is it possible to back transform confidence intervals for using the plot_model argument? An additional question I have is how to define manually the color scale and order the factors using sjplot.
Hello all!
I am having two isues with the sjplot package, When dealing with my data I have the following issue:
Original data: https://docs.google.com/spreadsheets/d/1hoOfh78Ev03amXYwNxlWpwbdr1GcDtL_QBiErwxcJds/edit?usp=sharing library(ggplot2) library(geepack) library(sjPlot)
dat2<-read.delim("clipboard")#Copiar los datos en el portapapeles dat$IDN=as.factor(dat$IDN) attach(dat2)
m11 <- geeglm( formula = log(Timmo)~ presa+picaduras, data = dat2, id = IDN, corstr = "exchangeable" ) plot_model(m11, type = "pred", terms = c("picaduras", "presa"))
When plotting the data I get this error: # Model has log-transformed response. Back-transforming predictions to original response scale. Standard errors are still on the log-scale
My question is, is it possible to back transform confidence intervals for using the plot_model argument? An additional question I have is how to define manually the color scale and order the factors using sjplot.
Thanks for sharing this package, it is awesome!
Many thanks