Description Usage Arguments Value Examples

`ggpoly()`

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

1 |

`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 |

`ci.lvl` |
Numeric, the level of the confidence intervals. For |

`...` |
Further arguments passed down to |

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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
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)
``` |

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