On Thu, 30 Jul 2009, Mark Na wrote:
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;
Fit the model without the "year" effect and compare both fits with
anova().
b) the significance of each year vis-a-vis every other year (the model
output only tests each year against the baseline year).
If you want to compare every year with the next year, you can use
successive difference contrasts for year. These are available as
contr.sdif() in MASS.
If you want to perform all possible pairwise comparisons, i.e., Tukey
contrasts, you can use glht() from package "multcomp". See the package
documentation and vignette for further examples.
hth,
Z
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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