predict_plot: Prediction Plot

In ztils: Various Common Statistical Utilities

Prediction Plot

Description

This function uses a model, dataframe, and supplied predictor, response, and group variables to make predictions based off the model over a user-defined length with options to predict over the confidence or prediction interval and to apply a mathematical correction. It then graphs both the real data and the specified interval using 'ggplot2'. You can also choose the color palette from 'scico' palettes.

Usage

predict_plot(
  mod,
  data,
  rvar,
  pvar,
  group = NULL,
  length = 50,
  interval = "confidence",
  correction = "normal",
  palette = "oslo"
)

Arguments

mod	the model used for predictions
data	the data used to render the "real" points on the graph and for aggregating groups to determine prediction limits (should be the same as the data used in the model)
rvar	the response variable (y variable / variable the model is predicting)
pvar	the predictor variable (x variable / variable the model will predict against)
group	the group; should be a factor; one response curve will be made for each group
length	the length of the variable over which to predict (higher = more resolution, essentially)
interval	the type of interval to predict ("confidence" or "prediction")
correction	the type of correction to apply to the prediction ("normal", "exponential", or "logit")
palette	the color palette used to color the graph, with each group corresponding to a color

Value

A plot showing the real data and the model's predicted 95% CI or PI over a number of groups, with optional corrections.

Examples

## Example 1
mod1 <- lm(Sepal.Length ~ Petal.Length + Species, data = iris)
predict_plot(mod1, iris, Sepal.Length, Petal.Length, Species)

ztils documentation built on April 11, 2025, 5:52 p.m.