Calculate the effect of an independent variable on a dependent variable conditional on the values of a (continous) moderator variable to perform a floodlight analysis Spiller2013cSEM. Moreover, the Johnson-Neyman points are calculated, i.e. the value(s) of the moderator for which lower or upper boundary of the confidence interval of the effect estimate of the independent variable on the depedent variable switches signs.
doFloodlightAnalysis(
.object = NULL,
.alpha = 0.05,
.dependent = NULL,
.moderator = NULL,
.independent = NULL,
.n_steps = 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 steps, e.g., in
surface analysis or floodlight analysis the spotlights (= values of .moderator)
between min(.moderator) and max(.moderator) to use. Defaults to 100.
A list of class cSEMFloodlight with a corresponding method for plot().
See: plot.cSEMFloodlight().