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fortify.lm

Supplement the data fitted to a linear model with model fit statistics.


Description

If you have missing values in your model data, you may need to refit the model with na.action = na.exclude.

Usage

## S3 method for class 'lm'
fortify(model, data = model$model, ...)

Arguments

model

linear model

data

data set, defaults to data used to fit model

...

not used by this method

Value

The original data with extra columns:

.hat

Diagonal of the hat matrix

.sigma

Estimate of residual standard deviation when corresponding observation is dropped from model

.cooksd

Cooks distance, cooks.distance()

.fitted

Fitted values of model

.resid

Residuals

.stdresid

Standardised residuals

Examples

mod <- lm(mpg ~ wt, data = mtcars)
head(fortify(mod))
head(fortify(mod, mtcars))

plot(mod, which = 1)

ggplot(mod, aes(.fitted, .resid)) +
  geom_point() +
  geom_hline(yintercept = 0) +
  geom_smooth(se = FALSE)

ggplot(mod, aes(.fitted, .stdresid)) +
  geom_point() +
  geom_hline(yintercept = 0) +
  geom_smooth(se = FALSE)

ggplot(fortify(mod, mtcars), aes(.fitted, .stdresid)) +
  geom_point(aes(colour = factor(cyl)))

ggplot(fortify(mod, mtcars), aes(mpg, .stdresid)) +
  geom_point(aes(colour = factor(cyl)))

plot(mod, which = 2)
ggplot(mod) +
  stat_qq(aes(sample = .stdresid)) +
  geom_abline()

plot(mod, which = 3)
ggplot(mod, aes(.fitted, sqrt(abs(.stdresid)))) +
  geom_point() +
  geom_smooth(se = FALSE)

plot(mod, which = 4)
ggplot(mod, aes(seq_along(.cooksd), .cooksd)) +
  geom_col()

plot(mod, which = 5)
ggplot(mod, aes(.hat, .stdresid)) +
  geom_vline(size = 2, colour = "white", xintercept = 0) +
  geom_hline(size = 2, colour = "white", yintercept = 0) +
  geom_point() + geom_smooth(se = FALSE)

ggplot(mod, aes(.hat, .stdresid)) +
  geom_point(aes(size = .cooksd)) +
  geom_smooth(se = FALSE, size = 0.5)

plot(mod, which = 6)
ggplot(mod, aes(.hat, .cooksd)) +
  geom_vline(xintercept = 0, colour = NA) +
  geom_abline(slope = seq(0, 3, by = 0.5), colour = "white") +
  geom_smooth(se = FALSE) +
  geom_point()

ggplot(mod, aes(.hat, .cooksd)) +
  geom_point(aes(size = .cooksd / .hat)) +
  scale_size_area()

ggplot2

Create Elegant Data Visualisations Using the Grammar of Graphics

v3.3.3
MIT + file LICENSE
Authors
Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), Winston Chang [aut] (<https://orcid.org/0000-0002-1576-2126>), Lionel Henry [aut], Thomas Lin Pedersen [aut, cre] (<https://orcid.org/0000-0002-5147-4711>), Kohske Takahashi [aut], Claus Wilke [aut] (<https://orcid.org/0000-0002-7470-9261>), Kara Woo [aut] (<https://orcid.org/0000-0002-5125-4188>), Hiroaki Yutani [aut] (<https://orcid.org/0000-0002-3385-7233>), Dewey Dunnington [aut] (<https://orcid.org/0000-0002-9415-4582>), RStudio [cph, fnd]
Initial release

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