Description Usage Arguments Details Value Author(s) References Examples
Generates two conditional effects plots for two interacted continuous covariates in linear models.
1 2 3 4 5 6 7 8 9 |
obj |
A model object of class |
varnames |
A two-element character vector where each element is the name of a variable involved in a two-way interaction. |
varcov |
A variance-covariance 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 x-labels 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 y-labels 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,
63-82.
Berry, W., M. Golder and D. Milton. (2012) Improving Tests of
Theories Positing Interactions. Journal of Politics.
1 2 3 | data(InteractionEx)
mod <- lm(y ~ x1*x2 + z, data=InteractionEx)
DAintfun3(mod, c("x1", "x2"))
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