ggpoly: Get marginal effects for polynomial terms

Description Usage Arguments Value Examples

View source: R/ggpoly.R

Description

ggpoly() computes marginal effects for polynomial terms. The result is returned as tidy data frame.

Usage

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ggpoly(model, poly.term, ci.lvl = 0.95, ...)

Arguments

model

A fitted model object, or a list of model objects. Any model that is supported by the effects-package should work.

poly.term

Name of the polynomial term in model, as string.

ci.lvl

Numeric, the level of the confidence intervals. For ggpredict(), use ci.lvl = NA, if confidence intervals should not be calculated (for instance, due to computation time).

...

Further arguments passed down to effect.

Value

A tibble (with ggeffects class attribute) with consistent data columns:

x

the values of the first term in terms, used as x-position in plots.

predicted

the predicted values, used as y-position in plots.

conf.low

the lower bound of the confidence interval for the predicted values.

conf.high

the upper bound of the confidence interval for the predicted values.

group

the grouping level from the second term in terms, used as grouping-aesthetics in plots.

Examples

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data(efc)
fit <- lm(
  tot_sc_e ~ c12hour + e42dep + e17age + I(e17age^2) + I(e17age^3),
  data = efc
)
dat <- ggpoly(fit, "e17age")

# this would give the same result
ggpredict(fit, "e17age")

library(ggplot2)
ggplot(dat, aes(x, predicted)) +
  stat_smooth(se = FALSE) +
  geom_ribbon(aes(ymin = conf.low, ymax = conf.high), alpha = .15) +
  labs(x = get_x_title(dat), y = get_y_title(dat))

## Not run: 
# or:
plot(dat)
## End(Not run)

strengejacke/ggtidyr documentation built on May 26, 2017, 9:58 p.m.