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 [[alternative HTML version deleted]]
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