simple_slope.Rd
The function uses the interaction::sim_slopes()
to calculate the slope estimate at varying level of moderators (+/- 1 SD and mean).
Additionally, it will produce a Johnson-Newman plot that shows when the slope estimate is not significant
simple_slope(
data,
model,
two_way_interaction_factor = NULL,
three_way_interaction_factor = NULL
)
data frame
model object from lm
, lme
,lmer
vector of character of the two_way_interaction_factor
vector of character of the three_way_interaction_factor
a list with the slope estimate data frame and a Johnson-Newman plot.
fit <- lm_model(
data = iris,
response_variable = Sepal.Length,
predictor_variable = tidyselect::everything(),
three_way_interaction_factor = c(Sepal.Width, Petal.Width, Petal.Length)
)
#> Warning: The following columns are coerced into numeric: Species
#> Fitting Model with lm:
#> Formula = Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width + Species + Sepal.Width*Petal.Width*Petal.Length
simple_slope_fit <- simple_slope(
data = iris,
model = fit,
three_way_interaction_factor = c("Sepal.Width", "Petal.Width", "Petal.Length")
)