DAintfun3 {DAMisc}  R Documentation 
Generates two conditional effects plots for two interacted continuous covariates in linear models.
DAintfun3(
obj,
varnames,
varcov = NULL,
name.stem = "cond_eff",
xlab = NULL,
ylab = NULL,
plot.type = "screen"
)
obj 
A model object of class 
varnames 
A twoelement character vector where each element is the name of a variable involved in a twoway interaction. 
varcov 
A variancecovariance matrix with which to calculate the
conditional standard errors. If 
name.stem 
A character string giving filename to which the appropriate extension will be appended 
xlab 
Optional vector of length two giving the xlabels for the two
plots that are generated. The first element of the vector corresponds to
the figure plotting the conditional effect of the first variable in

ylab 
Optional vector of length two giving the ylabels for the two
plots that are generated. The first element of the vector corresponds to
the figure plotting the conditional effect of the first variable in

plot.type 
One of ‘pdf’, ‘png’, ‘eps’ or
‘screen’, where the one of the first three will produce two graphs
starting with 
This function does the same thing as DAintfun2
, but presents
effects only at the mean of the conditioning variable and the mean +/ 1
standard deviation.
graphs 
Either a single graph is printed on the screen (using

Dave Armstrong
Brambor, T., W.R. Clark and M. Golder. (2006) Understanding
Interaction Models: Improving Empirical Analyses. Political Analysis 14,
6382.
Berry, W., M. Golder and D. Milton. (2012) Improving Tests of
Theories Positing Interactions. Journal of Politics.
data(InteractionEx)
mod < lm(y ~ x1*x2 + z, data=InteractionEx)
DAintfun3(mod, c("x1", "x2"))