I have the following model and have used the effects package to plot the predicted probabilities and the confidence interval lines. However, I was wondering how I'd go about spitting out a data frame in R which has the response value, the low and high ci values, and the predicted values. Kind of like the following
mod1 = glm(won_ping ~ our_bid, data=ndat, family=binomial(link="probit"))
summary(mod1)
library(effects)
plot(effect("our_bid", mod1), rescale.axis=FALSE, multiline=TRUE, xlim=c(0,2000), main="129- AH - Bid model")
Desired output with our response variable and the confidence intervals for the predicted probabilities:
our bid low_ci hi_ci prob
1 0.15 0.21 0.17
2 0.18 0.23 0.20
3 0.20 0.30 0.25
4 0.21 0.25 0.23
...
How would I go about getting the following result in R.
I tried the following but it doesn't work as I want the probabilities and not the log-odds values.
> as.data.frame(effect("our_bid", mod1))
our_bid fit se lower upper
1 25 -2.3549908 0.04598536 -2.44512045 -2.2648612
2 238 -2.0297771 0.03794491 -2.10414781 -1.9554065
3 451 -1.7045635 0.03724233 -1.77755712 -1.6315699
4 664 -1.3793498 0.04422870 -1.46603649 -1.2926632
5 877 -1.0541362 0.05610148 -1.16409305 -0.9441793
6 1090 -0.7289225 0.07043143 -0.86696557 -0.5908795
7 1303 -0.4037089 0.08599888 -0.57226356 -0.2351541
8 1516 -0.0784952 0.10224011 -0.27888213 0.1218917
9 1729 0.2467185 0.11887929 0.01371934 0.4797176
10 1942 0.5719321 0.13577018 0.30582746 0.8380368