The interpretation of lm(y~x)?
Have you read An Introduction to R or other R tutorial? DO you know about ordered factors and contrasts in linear models? -- Bert
On Wed, Feb 6, 2013 at 5:00 AM, jing tang <gimmytang at gmail.com> wrote:
Hi,
I am reading the book "Mixed Effects Models in S and S-Plus" and come
across an example with the Rail data.
I tried to use lm(travel~Rail,data=Rail) and got the following result:
Call:
lm(formula = travel ~ Rail, data = Rail)
Residuals:
Min 1Q Median 3Q Max
-6.6667 -1.0000 0.1667 1.0000 6.3333
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 66.5000 0.9477 70.169 < 2e-16 ***
Rail.L 54.3032 2.3214 23.392 2.22e-11 ***
Rail.Q -4.6917 2.3214 -2.021 0.066161 .
Rail.C -2.6584 2.3214 -1.145 0.274458
Rail^4 -0.5669 2.3214 -0.244 0.811181
Rail^5 11.1919 2.3214 4.821 0.000418 ***
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
I wonder how the model is represented. Is it correct to write: Travel =
beta1 + beta2*Rail + error? Beta1 should be Intercept which is clear to me.
But how to link beta2 with the coefficients Rail.L, Rail.Q, Rail.C, Rail^4
and Rail^5 shown in the result?
Thanks for your comments,
Best,
Jing
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Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm