summary(my_lm) will give you t-values, anova(my_lm) will give you
(equivalent) F-values. summary() might be preferred because it also
provides the estimates & SE.
> a=data.frame(dv=rnorm(10),iv1=rnorm(10),iv2=rnorm(10))
> my_lm=lm(dv~iv1*iv2,a)
> summary(my_lm)
Call:
lm(formula = dv ~ iv1 * iv2, data = a)
Residuals:
Min 1Q Median 3Q Max
-1.8484 -0.2059 0.1627 0.4623 1.0401
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.4864 0.4007 -1.214 0.270
iv1 0.8233 0.5538 1.487 0.188
iv2 0.2314 0.3863 0.599 0.571
iv1:iv2 -0.4110 0.5713 -0.719 0.499
Residual standard error: 1.017 on 6 degrees of freedom
Multiple R-squared: 0.3161, Adjusted R-squared: -0.02592
F-statistic: 0.9242 on 3 and 6 DF, p-value: 0.4842
> anova(my_lm)
Analysis of Variance Table
Response: dv
Df Sum Sq Mean Sq F value Pr(>F)
iv1 1 1.9149 1.9149 1.8530 0.2223
iv2 1 0.4156 0.4156 0.4021 0.5494
iv1:iv2 1 0.5348 0.5348 0.5175 0.4990
Residuals 6 6.2004 1.0334
On Thu, Apr 16, 2009 at 10:35 AM, kayj <kjaj...@yahoo.com> wrote:
>
> Hi,
>
>
> How can I find the p-value for the F test for the interaction terms in a
> regression linear model lm ?
>
> I appreciate your help
>
>
> --
> View this message in context:
> http://www.nabble.com/F-test-tp23078122p23078122.html
> Sent from the R help mailing list archive at Nabble.com.
>
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>
--
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University
Looking to arrange a meeting? Check my public calendar:
http://tr.im/mikes_public_calendar
~ Certainty is folly... I think. ~
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