Calculate the effect of an independent variable (z) on a dependent variable (y) conditional on the values of a (continous) moderator variable (x) to perform a floodlight analysis Spiller2013cSEM. Moreover, the Johnson-Neyman points are calculated, i.e. the value(s) of x for which lower or upper boundary of the confidence interval of the effect estimate of z for a given x switch signs.
doFloodlightAnalysis(
.object = NULL,
.alpha = 0.05,
.y = NULL,
.x = NULL,
.z = NULL,
.n_spotlights = 100
)
An R object of class cSEMResults resulting from a call to csem()
.
An integer or a numeric vector of significance levels.
Defaults to 0.05
.
Character string. The name of the dependent variable. Defaults to NULL
.
Character string. The name of the moderator variable. Defaults to NULL
.
Character string. The name of the independent variable. Defaults to NULL
.
Integer. A numeric value giving the number of spotlights (= values of .z)
between min(.z) and max(.z) to use. Defaults to 100
.
A list of class cSEMFloodlight
with a corresponding method for plot()
.
See: plot.cSEMFloodlight()
.