Description Usage Arguments Value References Examples
Probe moderation effect using the Johnson-Neyman technique
1 | jn(model, dv, iv, mod, mrange, alpha = 0.05, yas = "none")
|
model |
Regression model (lm, glm, list). |
dv |
Dependent variable (character). |
iv |
Independent variable (character). |
mod |
Moderator variable(s) (character or character vector). |
mrange |
Range of values that jn should examine for moderator variable. Uses the current range of moderator values by default (numeric vector). |
alpha |
Alpha level to use (numeric). |
yas |
Show y (or conditional effect) as: |
A list with the elements
Spiller, S. A., Fitzsimons, G. J., Lynch, J. G., Jr, & McClelland, G. H. (2013). Spotlights, floodlights, and the magic number zero: Simple effects tests in moderated regression. Journal of Marketing Research, 50(2), 277-288.
Bauer, D. J., & Curran, P. J. (2005). Probing interactions in fixed and multilevel regression: Inferential and graphical techniques. Multivariate Behavioral Research, 40(3), 373-400.
1 2 3 4 5 6 7 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.