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smsfrn avatar smsfrn commented on July 17, 2024

This works for saving one-off plots, but I'm still hoping to access the plot directly from the plotResiduals() object to support more complex workflows (i.e. looping through multiple predictors, saving the residual plot for each in a list, and generating a gridded figure with all the plots).

library(tidyverse)
library(lme4)
library(DHARMa)
library(here)

dat <- iris %>%
  mutate(Petal.Length_factor = ifelse(Petal.Length < 4.2, "A", "B"))

mod <- lme4::lmer(Sepal.Width ~ Species + Petal.Width + (1 | Petal.Length_factor),
                  data = dat)

simulationOutput <- simulateResiduals(fittedModel = mod)

var <- "Petal.Width"

output_path <- here(paste0("residual_plot_", var, ".png"))

png(output_path)
plotResiduals(simulationOutput, dat %>% pull(var))
dev.off()

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florianhartig avatar florianhartig commented on July 17, 2024

Hello Sam,

can you give me an example of another plotting function where this works?

Note that DHARMa is using base R and and not ggplot for plotting

Best,
F

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smsfrn avatar smsfrn commented on July 17, 2024

Oops, nope. I misremembered what could be done with base graphics. I'll close this!

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