mclogit: predict – R documentation

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predict

Predicting responses or linear parts of the baseline-category and conditional logit models

Description

The predict() methods allow to obtain within-sample and out-of-sample predictions from models fitted with mclogit() and mblogit().

For models with random effecs fitted using the PQL-method, it is possible to obtain responses that are conditional on the reconstructed random effects.

Usage

## S3 method for class 'mblogit'
predict(object, newdata=NULL,type=c("link","response"),se.fit=FALSE, ...)
## S3 method for class 'mclogit'
predict(object, newdata=NULL,type=c("link","response"),se.fit=FALSE, ...)
## S3 method for class 'mmblogit'
predict(object, newdata=NULL,type=c("link","response"),se.fit=FALSE,
                             conditional=TRUE, ...)
## S3 method for class 'mmclogit'
predict(object, newdata=NULL,type=c("link","response"),se.fit=FALSE,
                             conditional=TRUE, ...)

Arguments

`object`	an object in class "mblogit", "mmblogit", "mclogit", or "mmclogit"
`newdata`	an optional data frame with new data
`type`	a character string specifying the kind of prediction
`se.fit`	a logical value; whether predictions should be accompanied with standard errors
`conditional`	a logical value; whether predictions should be made conditional on the random effects (or whether they are set to zero, i.e. their expectation). This argument is consequential only if the "mmblogit" or "mmclogit" object was created with `method="PQL"`.
`...`	other arguments, ignored.

Value

The predict methods return either a matrix (unless called with se.fit=TRUE) or a list with two matrix-valued elements "fit" and "se.fit".

Examples

library(MASS)
(house.mblogit <- mblogit(Sat ~ Infl + Type + Cont, 
                          data = housing,
                          weights=Freq))

head(pred.house.mblogit <- predict(house.mblogit))
str(pred.house.mblogit <- predict(house.mblogit,se=TRUE))

head(pred.house.mblogit <- predict(house.mblogit,
                                   type="response"))
str(pred.house.mblogit <- predict(house.mblogit,se=TRUE,
                                  type="response"))
 # This takes a bit longer.
data(electors)
(mcre <- mclogit(
    cbind(Freq,interaction(time,class))~econ.left/class+welfare/class+auth/class,
    random=~1|party.time,
    data=within(electors,party.time<-interaction(party,time))))

str(predict(mcre))
str(predict(mcre,type="response"))

str(predict(mcre,se.fit=TRUE))
str(predict(mcre,type="response",se.fit=TRUE))

mclogit

Multinomial Logit Models, with or without Random Effects or Overdispersion

v0.8.7.3

GPL-2

Authors

Martin Elff

Initial release

2021-03-19