[R] How to get predicted values of y for different x values?

[Daniel Malter]

Please read the posting guide (requires a self-contained example of code) and
consult the help pages before posting. If you type ?predict.lm the help page
clearly states that the argument 'newdata' takes "[a]n optional data frame
in which to look for variables with which to predict..."

x1<-rnorm(100)
x2<-rnorm(100)
e<-rnorm(100)
y<-x1+x2+x1*x2+e
reg<-lm(y~x1*x2)
summary(reg)
predict(reg,newdata=data.frame(x1=2,x2=2)) 

HTH,
Daniel


halptekin wrote:
> 
> Here is my model with interaction terms and control variables (I changed
> variables names for easy read): 
> 
> reg1 <- lm(y ~ x1*x2*x3 +control1 + control2 + control3) 
> 
> x1 ranges from 0 to 6; x2 from 0 to 5; and x3 from 0 to 4. All three are
> discrete ordinal variables; but I will treat them as continuous variables. 
> (a) How can I see the predicted values of y for each of these scenarios
> (210 y values I guess)? 
> (b) How can I see the predicted value of y for the minimum and maximum
> values of x1, x2, and x3 (8 y values)? 
> (c) How can I see the predicted value of y for x1=6; x2=5; and x3=4 (only
> one y value)?
> 

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