On Jul 19, 2011, at 2:36 PM, Jeff Newmiller wrote:
?predict
Use data.frame() to generate input vectors (newdata) for which you
want predicted values.
The OP probably needs to use expand.grid to generate the spanning
combinations of x values. He will in addition need to include values
for "control" variables.
dfrm <- expand.grid(x1 = 0: 6, x2 = 0: 5, x3 = 0 : 4)
dfrm$control1 <- <some value of same class as original control1 data>
repeat x 2
--
David.
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Sent from my phone. Please excuse my brevity.
halptekin <halpte...@gmail.com> 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
scenarios I guess)?
(b) How can I see the predicted value of y for the minimum and maximum
values of x1, x2, and x3 (8 scenarios)?
(c) How can I see the predicted value of y for x1=6; x2=5; and x3=4 (1
scenario)?
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David Winsemius, MD
West Hartford, CT
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