effectsplot {psychomix} | R Documentation |
Effects Displays for Concomitant Variables in Finite Mixture Models
Description
Generic function for visualizing the effects of concomitant variables in finite mixture models.
Usage
effectsplot(object, ...)
Arguments
object |
Fitted model object. |
... |
Arguments passed to |
Details
effectsplot
is set up to be both an S3 and S4 generic.
The idea is that it provides the glue needed to extract the concomitant
part from a mixture model: First, the concomitant model is
refitted as a multinom
object or glm
object (in case of
a mixture with two components). Second, effect
or allEffects
from the effects package
is called to extract the effects of the concomitants. Third,
the corresponding plot
methods from the effects
package create the display.
Currently, this is implemented for raschmix
,
btmix
, and mptmix
objects. The interface is not
yet fully tested and may change in future versions.
References
Fox, J. (2003). Effect Displays in R for Generalised Linear Models. Journal of Statistical Software, 8(15), 1–27. http://www.jstatsoft.org/v08/i15/
Fox, J., and Hong, J. (2009). Effect Displays in R for Multinomial and Proportional-Odds Logit Models: Extensions to the effects Package. Journal of Statistical Software, 32(1), 1–24. http://www.jstatsoft.org/v32/i01/
See Also
effect
, allEffects
,
multinom
, glm
Examples
## data on party preferences in Germany
## (omit single observation with education = 1)
data("GermanParties2009", package = "psychotools")
gp <- subset(GermanParties2009, education != "1")
gp$education <- factor(gp$education)
## fit Bradley-Terry mixture, see ?btmix for more details
## and a fully-worked example
suppressWarnings(RNGversion("3.5.0"))
set.seed(2)
cm4 <- btmix(preference ~ gender + education + age + crisis, data = gp, k = 4, nrep = 1)
## inspect mixture and effects
library("lattice")
xyplot(cm4)
effectsplot(cm4)
## vis effects package directly
if(require("effects")) {
eff4 <- allEffects(cm4)
plot(eff4)
}