Do a floodlight analysis

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.

 .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().


See Also

csem(), cSEMResults, plot.cSEMFloodlight()

  • doFloodlightAnalysis
Documentation reproduced from package cSEM, version 0.1.0, License: GPL-3

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