# NOT RUN {
## Estimate blackbox object from example and call predict function
data(Issues1980)
Issues1980[Issues1980[,"abortion1"]==7,"abortion1"] <- 8 #missing recode
Issues1980[Issues1980[,"abortion2"]==7,"abortion2"] <- 8 #missing recode
### This command conducts estimates, which we instead load using data()
# Issues1980_bb <- blackbox(Issues1980,missing=c(0,8,9),verbose=FALSE,dims=3,minscale=8)
data(Issues1980_bb)
prediction <- predict.blackbox(Issues1980_bb,dims=3)
## Examine predicted vs. observed values for first 10 respondents
## Note that 4th and 6th respondents are NA because of missing data
Issues1980[1:10,]
prediction[1:10,]
## Check correlation across all predicted vs. observed, excluding missing values
prediction[which(Issues1980 %in% c(0,8,9))] <- NA
cor(as.numeric(prediction), as.numeric(Issues1980), use="pairwise.complete")
# }
Run the code above in your browser using DataLab