psycModel (version 0.5.0)

three_way_interaction_plot: Three-way Interaction Plot

Description

The function creates a two-way interaction plot. It will creates a plot with ± 1 SD from the mean of the independent variable. See below for supported model. I recommend using concurrently with lm_model(), lme_model().

Usage

three_way_interaction_plot(
  model,
  data = NULL,
  cateogrical_var = NULL,
  graph_label_name = NULL,
  y_lim = NULL,
  plot_color = FALSE
)

Value

a ggplot object

Arguments

model

object from lme, lme4, lmerTest object.

data

data.frame. If the function is unable to extract data frame from the object, then you may need to pass it directly

cateogrical_var

list. Specify the upper bound and lower bound directly instead of using ± 1 SD from the mean. Passed in the form of list(var_name1 = c(upper_bound1, lower_bound1),var_name2 = c(upper_bound2, lower_bound2))

graph_label_name

vector of length 4 or a switch function (see ?two_way_interaction_plot example). Vector should be passed in the form of c(response_var, predict_var1, predict_var2, predict_var3).

y_lim

the plot's upper and lower limit for the y-axis. Length of 2. Example: c(lower_limit, upper_limit)

plot_color

default if FALSE. Set to TRUE if you want to plot in color

Details

It appears that ``predict` cannot handle categorical factors. All variables are converted to numeric before plotting.

Examples

lm_fit <- lm(Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width +
  Sepal.Width:Petal.Length:Petal.Width, data = iris)

three_way_interaction_plot(lm_fit, data = iris)