Given a design matrix, as generated by the design.des function, the design.dat function appends (1) fitted values on the response scale (“fitted”), (2) the delta method standard error for the fitted value (“se”), (3) the lower limit of a confidence interval around the fitted value (“ll”), and the upper limit of a confidence interval around the fitted value (“ul”).
For example:
library(catregs)
data("Mize19AH")
m1 <- glm(alcB ~woman*parrole + age + race2 + race3 + race4 + income + ed1 + ed2 + ed3 + ed4,family="binomial",data=Mize19AH)
des2<-margins.des(m1,expand.grid(woman=c(0,1),parrole=c(0,1)))
margins.dat(m1,des2,rounded=5)## woman parrole age race2 race3 race4 income ed1 ed2 ed3
## 1 0 0 28.41653 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 2 1 0 28.41653 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 3 0 1 28.41653 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 4 1 1 28.41653 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## ed4 fitted se ll ul
## 1 0.09775 0.72071 0.01277 0.69567 0.74574
## 2 0.09775 0.66015 0.01556 0.62966 0.69065
## 3 0.09775 0.61450 0.02024 0.57483 0.65416
## 4 0.09775 0.49175 0.01470 0.46293 0.52056## parrole woman age race2 race3 race4 income ed1 ed2 ed3
## 1 1 1 28.41653 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 2 1 1 28.41653 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 3 1 1 28.41653 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## ed4 fitted se ll ul
## 1 0.09775 0.49175 0.0147 0.46293 0.52056
## 2 0.09775 NA NA NA NA
## 3 0.09775 0.49175 0.0147 0.46293 0.52056des3 <- margins.des(m1,expand.grid(age=seq(20,75,5),parrole=c(0,1)))
a<- margins.dat(m1,des3,rounded=5)
a## age parrole woman race2 race3 race4 income ed1 ed2 ed3
## 1 20 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 2 25 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 3 30 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 4 35 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 5 40 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 6 45 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 7 50 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 8 55 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 9 60 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 10 65 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 11 70 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 12 75 0 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 13 20 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 14 25 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 15 30 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 16 35 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 17 40 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 18 45 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 19 50 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 20 55 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 21 60 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 22 65 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 23 70 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## 24 75 1 0.54748 0.21895 0.0058 0.02995 34.50605 0.1811 0.41003 0.25424
## ed4 fitted se ll ul
## 1 0.09775 0.82016 0.02367 0.77376 0.86656
## 2 0.09775 0.74777 0.01437 0.71961 0.77593
## 3 0.09775 0.65839 0.01302 0.63286 0.68391
## 4 0.09775 0.55613 0.03349 0.49048 0.62177
## 5 0.09775 0.44888 0.05585 0.33941 0.55835
## 6 0.09775 0.34618 0.07195 0.20516 0.48720
## 7 0.09775 0.25606 0.07823 0.10274 0.40939
## 8 0.09775 0.18285 0.07526 0.03534 0.33036
## 9 0.09775 0.12699 0.06618 -0.00272 0.25670
## 10 0.09775 0.08639 0.05448 -0.02039 0.19317
## 11 0.09775 0.05791 0.04275 -0.02588 0.14171
## 12 0.09775 0.03843 0.03241 -0.02509 0.10194
## 13 0.09775 0.71460 0.03507 0.64586 0.78335
## 14 0.09775 0.61944 0.02042 0.57943 0.65946
## 15 0.09775 0.51413 0.01353 0.48760 0.54065
## 16 0.09775 0.40754 0.03042 0.34791 0.46717
## 17 0.09775 0.30900 0.04596 0.21893 0.39908
## 18 0.09775 0.22523 0.05358 0.12021 0.33025
## 19 0.09775 0.15894 0.05343 0.05422 0.26367
## 20 0.09775 0.10941 0.04801 0.01532 0.20351
## 21 0.09775 0.07396 0.04012 -0.00468 0.15260
## 22 0.09775 0.04936 0.03186 -0.01310 0.11181
## 23 0.09775 0.03265 0.02440 -0.01517 0.08047
## 24 0.09775 0.02147 0.01819 -0.01418 0.05712
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