probe_interaction  R Documentation 
probe_interaction
is a convenience function that allows users to call
both sim_slopes
and interact_plot
with a single
call.
probe_interaction(model, pred, modx, mod2 = NULL, ...)
model 
A regression model. The function is tested with 
pred 
The name of the predictor variable involved
in the interaction. This can be a bare name or string. Note that it
is evaluated using 
modx 
The name of the moderator variable involved
in the interaction. This can be a bare name or string. The same

mod2 
Optional. The name of the second moderator
variable involved in the interaction. This can be a bare name or string.
The same 
... 
Other arguments accepted by 
This function simply merges the nearlyequivalent arguments needed to call
both sim_slopes
and interact_plot
without the
need for retyping their common arguments. Note that each function is called
separately and they refit a separate model for each level of each
moderator; therefore, the runtime may be considerably longer than the
original model fit. For larger models, this is worth keeping in mind.
Sometimes, you may want different parameters when doing simple slopes analysis compared to when plotting interaction effects. For instance, it is often easier to interpret the regression output when variables are standardized; but plots are often easier to understand when the variables are in their original units of measure.
probe_interaction
does not
support providing different arguments to each function. If that is needed,
use sim_slopes
and interact_plot
directly.
simslopes 
The 
interactplot 
The 
Jacob Long jacob.long@sc.edu
Other interaction tools:
johnson_neyman()
,
sim_margins()
,
sim_slopes()
# Using a fitted model as formula input
fiti < lm(Income ~ Frost + Murder * Illiteracy,
data=as.data.frame(state.x77))
probe_interaction(model = fiti, pred = Murder, modx = Illiteracy,
modx.values = "plusminus")
# 3way interaction
fiti3 < lm(Income ~ Frost * Murder * Illiteracy,
data=as.data.frame(state.x77))
probe_interaction(model = fiti3, pred = Murder, modx = Illiteracy,
mod2 = Frost, mod2.values = "plusminus")
# With svyglm
if (requireNamespace("survey")) {
library(survey)
data(api)
dstrat < svydesign(id = ~1, strata = ~stype, weights = ~pw,
data = apistrat, fpc = ~fpc)
regmodel < svyglm(api00 ~ ell * meals + sch.wide, design = dstrat)
probe_interaction(model = regmodel, pred = ell, modx = meals,
modx.values = "plusminus", cond.int = TRUE)
# 3way with survey and factor input
regmodel3 < svyglm(api00 ~ ell * meals * sch.wide, design = dstrat)
probe_interaction(model = regmodel3, pred = ell, modx = meals,
mod2 = sch.wide)
# Can try different configurations of 1st vs 2nd mod
probe_interaction(model = regmodel3, pred = ell, modx = sch.wide,
mod2 = meals)
}
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