library(lme4)
testData = createData(sampleSize = 100, overdispersion = 0.5, family = poisson())
fittedModel <- glmer(observedResponse ~ Environment1 + (1|group),
family = "poisson", data = testData)
simulationOutput <- simulateResiduals(fittedModel = fittedModel)
# standard plot
plot(simulationOutput)
# one of the possible test, for other options see ?testResiduals / vignette
testDispersion(simulationOutput)
# the calculated residuals can be accessed via
residuals(simulationOutput)
# transform residuals to other pdf, see ?residuals.DHARMa for details
residuals(simulationOutput, quantileFunction = qnorm, outlierValues = c(-7,7))
# get residuals that are outside the simulation envelope
outliers(simulationOutput)
# calculating aggregated residuals per group
simulationOutput2 = recalculateResiduals(simulationOutput, group = testData$group)
plot(simulationOutput2, quantreg = FALSE)
# calculating residuals only for subset of the data
simulationOutput3 = recalculateResiduals(simulationOutput, sel = testData$group == 1 )
plot(simulationOutput3, quantreg = FALSE)
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