margins.dat.clogit

Computes predicted probabilities for conditional and rank-order/exploded logistic regression models. Inference is based upon simulation techniques. Alternatively, bootstrapping is an option for conditional logistic regression models.

library(catregs)
library(Epi)
data("LF06travel")
m1 <- clogistic(choice ~ train + bus + time  + invc, strata=id, data=LF06travel)
design <- data.frame(train=c(0,0,1),bus=c(0,1,0),time=200,invc=20)
design

##   train bus time invc
## 1     0   0  200   20
## 2     0   1  200   20
## 3     1   0  200   20

margins.dat.clogit(m1,design)

##   train bus time invc    lp probs    ll    ul    se
## 1     0   0  200   20 0.008  0.05 0.023 0.101 0.021
## 2     0   1  200   20 0.036  0.22 0.123 0.348 0.057
## 3     1   0  200   20 0.120  0.73 0.588 0.840 0.066

ma1<-margins.dat.clogit(m1,design,run.boot="yes")
names(ma1)

## [1] "des"       "boot.dist"

ma1$des

##   train bus time invc    lp probs    ll    ul    se ll.boot ul.boot
## 1     0   0  200   20 0.008  0.05 0.023 0.101 0.021   0.021   0.021
## 2     0   1  200   20 0.036  0.22 0.123 0.348 0.057   0.057   0.057
## 3     1   0  200   20 0.120  0.73 0.588 0.840 0.066   0.066   0.066