Howdy
I apologize for duplicated posting. But I decided to correct my previous
posting.
I had the regression results using
r <- lm(Y ~ nemp + as.factor(devt), data=d).
First, there is the result of anova(r). Here I could not find regression
coefficients.
Response: Y
Df Sum Sq Mean Sq F value Pr(>F)
nemp 1 58.2 58.2 1233.23 < 2e-16 ***
as.factor(devt) 3 3.6 1.2 25.69 2.6e-16 ***
Second, there is the result of summary(r) that I am confused
with too many coefficients for a factor variable "devt".
Because there are three coefficients for factor variables
such as"as.factor(devt)A ", "as.factor(devt)B", "as.factor(devt)C".
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) as.factor(devt1) 3 3.6 1.2
25.69 2.6e-16 *** 5.95e-02 10.19 < 2e-16 ***
nemp 2.87e-06 1.04e-07 27.63 < 2e-16 ***
as.factor(devt)A 2.44e-02 1.47e-02 1.66 0.09630 .
as.factor(devt)B -1.10e-01 1.40e-02 -7.90 4.6e-15 ***
as.factor(devt)C -9.19e-03 1.53e-02 -0.60 0.54953
Is this model right as a tentative model at least?
Y = 6.07e-01 + 2.87e-06* nemp + 2.44e-02 * as.factor(devt)A
- 1.10e-01 * as.factor(devt1)B - 9.19e-03 * as.factor(devt)C
And so, my question is "which coefficients should I use for a final
model?".
Thanks in advance,
--
Kum-Hoe Hwang, Ph.D.Phone : 82-31-250-3516Email : [EMAIL PROTECTED]
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