R help - Jul 2009 - Testing year effect in lm() ***failed first time, sending again

Dear R-helpers,

I have a linear model with a year effect (year is coded as a factor), i.e.
the parameter estimates for each level of my year variable have significant
P values (see some output below) and I am interested in testing:

a) the overall effect of year;
b) the significance of each year vis-a-vis every other year (the model
output only tests each year against the baseline year).

I'd appreciate any help with how to perform these post-hoc tests in R.

Many thanks,

Mark Na



Call:

lm(formula = data$SR.obs ~ log(data$AREA, 10) + data$YEAR,

    subset = (data$AREA >= 14.5))



Residuals:

    Min      1Q  Median      3Q     Max

-5.3412 -1.3140  0.1108  1.1972  4.3126



Coefficients:

                   Estimate Std. Error t value Pr(>|t|)

(Intercept)         -9.4606     0.6144 -15.399  < 2e-16 ***

log(data$AREA, 10)   3.9261     0.1734  22.644  < 2e-16 ***

data$YEAR2008        1.0750     0.2854   3.767 0.000211 ***

data$YEAR2009        1.5884     0.3073   5.169 5.18e-07 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1



Residual standard error: 1.822 on 226 degrees of freedom

Multiple R-squared: 0.6945, Adjusted R-squared: 0.6905

F-statistic: 171.3 on 3 and 226 DF,  p-value: < 2.2e-16



[1] "AIC=  934.557"

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Le jeudi 30 juillet 2009 ? 16:41 -0600, Mark Na a ?crit
:
> Dear R-helpers,
> 
> I have a linear model with a year effect (year is coded as a factor), i.e.
> the parameter estimates for each level of my year variable have significant
> P values (see some output below) and I am interested in testing:
> 
> a) the overall effect of year;
> b) the significance of each year vis-a-vis every other year (the model
> output only tests each year against the baseline year).
install.packges("multcomp")
help.start()

and use the vignettes ! They're good (and are a good complement to
somewhat incomplete  help pages : what in h*ll are valid arguments to
mcp() beyond "Tukey" ??? Curently, you'll have to dig in the
source to
learn that...).

HTH

					Emmanuel Charpentier