reghelper (version 0.3.3)

simple_slopes.merMod: Simple slopes of interaction.

Description

simple_slopes.merMod calculates all the simple effects of an interaction in a regression model.

Usage

# S3 method for merMod
simple_slopes(model, levels = NULL, ...)

Arguments

model

A fitted linear model of type 'merMod' with at least one interaction term.

levels

A list with element names corresponding to some or all of the variables in the model. Each list element should be a vector with the names of factor levels (for categorical variables) or numeric values (for continuous variables) at which to test that variable. Note: If you do not include 'sstest' as one of these levels, the function will not test the simple effects for that variable.

...

Not currently implemented; used to ensure consistency with S3 generic.

Value

A data frame with a row for each simple effect. The first few columns identify the level at which each variable in your model was set for that test. A 'sstest' value in a particular column indicates that this was the variable being tested. After columns for each variable, the data frame has columns for the slope of the test variable, the standard error, and t-value for the model.

Details

If the model includes interactions at different levels (e.g., three two-way interactions and one three-way interaction), the function will test the simple effects of the highest-order interaction. If there are multiple interactions in the highest order, it will test the first one in the model. If you wish to test simple effects for a different interaction, simply switch the order in the formula.

By default, this function will provide slopes at -1SD, the mean, and +1SD for continuous variables, and at each level of categorical variables. This can be overridden with the levels parameter.

If a categorical variable with more than two levels is being tested, you may see multiple rows for that test. One row will be shown for each contrast for that variable; the order is in the same order shown in contrasts().

See Also

simple_slopes.lm, simple_slopes.glm, simple_slopes.lme

Examples

# NOT RUN {
# iris data
if (require(lme4, quietly=TRUE)) {
    model <- lmer(Sepal.Width ~ Sepal.Length * Petal.Length + (1|Species), data=iris)
    summary(model)
    simple_slopes(model)
    simple_slopes(model,
        levels=list(Sepal.Length=c(4, 5, 6, 'sstest'),
        Petal.Length=c(2, 3, 'sstest')))  # test at specific levels
}
# }