Comments (5)
I have updated the documentation. Currently, model assumption functions should not return any plot, only the updated model with removed outliers. Perhaps this may be an option for future releases.
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I am not sure I understand this comment. Removed outliers?
sjp.glm produces a plot -- even if type="vif". The plot just is not returned. I can confirm that the documentation is consistent with the behaviour now. But I'd much prefer to have the ggplot object returned to be able to further tweak it to my needs.
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If you refer to the very last plot of model-assumptions, this is the same one as sjp.glm(fit)
. type = "ma"
first checks the model for outliers, and if there are any, they are being removed and an updated model w/o outliers is re-fitted. This updated glm
-object is returned. Set showOriginalModelOnly
to FALSE
to see plots for both models, original and updated.
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This is an example what should be possible, I'd say. And easy to achieve. Sorry, should have posted code right in the beginning:
# prepare dichotomous dependent variable
y <- ifelse(swiss$Fertility < median(swiss$Fertility), 0, 1)
# fit model
fitOR <- glm(y ~ swiss$Education + swiss$Examination + swiss$Infant.Mortality + swiss$Catholic,
family = binomial(link = "logit"))
sjp.glm(fitOR, type="vif")$plot + theme_bw()
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Sorry for confusion, I was talking about type = "ma"
, not type = "vif"
- my fault... Currently, you can get access to the plot only via last_plot()
function from ggplot. I re-open this issue and may add the plot as return value as well to that function.
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