| clRange {RSA} | R Documentation |
Range check for the CL/RRCL model
Description
Compute the regions of significance and test their intersection with the data
Usage
clRange(object, alpha = 0.05, verbose = TRUE, model = "CL")
Arguments
object |
An RSA object |
alpha |
Alpha level for the regions of significance of the surface's curvature |
verbose |
Should extra information be printed? |
model |
Either "CL" or "RRCL" |
Details
When testing a level-dependent congruence hypothesis with the CL or RRCL model, the clRange function helps to determine whether the hypothesis is supported for the whole range of realistic predictor combinations. It computes the mean predictor levels k1 and k2 at which the curvature of the surface changes its significance status. For each of the resulting intervals, the function informs whether the curvature is significantly negative, nonsignificant, or significantly positive in the respective interval.
When plotting the estimated model (CL or RRCL) with plot, you can plot the lines at which the significance status of the curvature changes and the surface above these lines by calling "K1" and "K2" in the options project and axes.
References
Humberg, S., Schönbrodt, F. D., Back, M. D., Nestler, S. (in preparation). Cubic response surface analysis: Investigating asymmetric and level-dependent congruence effects with third-order polynomial models. Manuscript submitted for publication.