Cross-validation on comparing linear models

I have 2 linear models to compare: One is reduced model and the other one is full model. I have already done F-Test on comparing 2 linear models. But I do not know how to do this using 5-fold cross-validation comparing 2 models. The following code is what I have in R.

library(carData) #make sure this package is installed!
data("Anscombe") #NOTE: lowercase was the data from before, uppercase is this dataset (annoying)
spending = subset(Anscombe,! rownames(Anscombe) %in% c("HI","AK","DC"),c(1,2,4)) ##Data file. 

mod_full = lm(education ~ urban + income, data=spending) ##Full model. 

mod_reduced = lm(education ~ income, data = spending) ## Reduced model. 

FTest = anova(mod_reduced, mod_full)
print(FTest) ##Print out the F-test result.