Dear All,
I have two factors: GROUP and PATIENT, where PATIENT is nested within
GROUP.
>levels(example$GROUP)
[1] "0" "1" "2" "3" "4"
> levels(example$PATIENT)
[1] "1" "2" "3"
There are three observations at each combination of these factors.
However, there are no observations for PATIENT = 3 and GROUP = 4.
> table(example$GROUP, example$PATIENT)
1 2 3
0 3 3 3
1 3 3 3
2 3 3 3
3 3 3 3
4 3 3 0
When I run an ANOVA on these factors
> fit <- lm(ABUNDANCE ~ GROUP + GROUP/PATIENT, data = example)
I receive an NA in the parameter estimate corresponding to missing
combination.
> summary(fit)
Call:
lm(formula = ABUNDANCE ~ GROUP + GROUP/PATIENT, data = example)
Residuals:
Min 1Q Median 3Q Max
-1.2985 -0.4284 0.1998 0.3663 0.8585
Coefficients: (1 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 13.18320 0.37333 35.312 <2e-16 ***
GROUP1 0.61861 0.52797 1.172 0.251
GROUP2 0.18993 0.52797 0.360 0.722
GROUP3 0.27163 0.52797 0.514 0.611
GROUP4 -0.28173 0.52797 -0.534 0.598
GROUP0:PATIENT2 0.12643 0.52797 0.239 0.812
GROUP1:PATIENT2 -0.72617 0.52797 -1.375 0.180
GROUP2:PATIENT2 -0.26360 0.52797 -0.499 0.621
GROUP3:PATIENT2 0.04293 0.52797 0.081 0.936
GROUP4:PATIENT2 0.59812 0.52797 1.133 0.267
GROUP0:PATIENT3 0.28147 0.52797 0.533 0.598
GROUP1:PATIENT3 -0.36452 0.52797 -0.690 0.496
GROUP2:PATIENT3 -0.34737 0.52797 -0.658 0.516
GROUP3:PATIENT3 -0.55119 0.52797 -1.044 0.305
GROUP4:PATIENT3 NA NA NA NA
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.6466 on 28 degrees of freedom
Multiple R-squared: 0.1867, Adjusted R-squared: -0.191
F-statistic: 0.4943 on 13 and 28 DF, p-value: 0.9093
I need to perform a contrast on various levels of GROUP/PATIENT, and
the NA prevents me from doing so. Is there a way to manipulate the
levels of the factors so that an NA is not present in the parameter
estimates?
Thanks,
Tim
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