Reputation: 8041
Quadratic terms are quite common in regression. Here is an example from John Fox (http://www.jstatsoft.org/v08/i15/paper)
library(car) # For data
library(splines) # For bs()
library(effects) # For plotting
data(Prestige)
prestige.mod <- lm(prestige ~ log(income) + bs(education, df=3) + poly(women, 2), data=Prestige)
summary(prestige.mod)
test <- plot(all.effects(prestige.mod, default.levels=50))
Is there any command in R to get the minimum/maximum of a quadratic effect right away without deriving in manually/plotting it?
Upvotes: 3
Views: 1196
Reputation: 263451
If I understand correctly I would be approximating value of "women" at which the "minimum effect" were to be found:
idx <- which.min( predict(prestige.mod, newdata= data.frame(
women=seq(min(Prestige$women), max(Prestige$women), length=100),
income=mean(Prestige$income, na.rm=TRUE),
education=mean(Prestige$education, na.rm=TRUE) ) ) )
idx
#37
#37
# Just copy the argument to the newdata argument in predict call above
# and get the value that produced the minimum
seq(min(Prestige$women), max(Prestige$women), length=100)[idx]
#[1] 35.45818
The use of the predict
function on value sequences contained in "newdata" dataframes is undoubtedly happening "underneath the hood" for the plotting of those "effects".
Upvotes: 1