What have you tried? I just did help.searhc(manova), which led me
to manova and summary.manova, which contained a balanced example, which
I unbalanced as follows:
tear - c(6.5, 6.2, 5.8, 6.5, 6.5, 6.9, 7.2, 6.9, 6.1, 6.3,
6.7, 6.6, 7.2, 7.1, 6.8, 7.1, 7.0, 7.2, 7.5, 7.6)
gloss - c(9.5, 9.9, 9.6, 9.6, 9.2, 9.1, 10.0, 9.9, 9.5, 9.4,
9.1, 9.3, 8.3, 8.4, 8.5, 9.2, 8.8, 9.7, 10.1, 9.2)
opacity - c(4.4, 6.4, 3.0, 4.1, 0.8, 5.7, 2.0, 3.9, 1.9, 5.7,
2.8, 4.1, 3.8, 1.6, 3.4, 8.4, 5.2, 6.9, 2.7, 1.9)
rate - factor(gl(2,10), labels=c(Low, High))
additive - factor(gl(2, 5, len=20), labels=c(Low, High))
DF - data.frame(tear, gloss, opacity, rate, additive)
fit - manova(cbind(tear, gloss, opacity) ~ rate * additive, DF)
f18 - manova(cbind(tear, gloss, opacity) ~ rate * additive, DF[1:18,])
summary(fit, test=Wilks) # ANOVA table of Wilks' lambda
summary(fit, test=Wilks) # ANOVA table of Wilks' lambda
Df Wilks approx F num Df den Df Pr(F)
rate 1 0.3819 7.5543 3 14 0.003034 **
additive 1 0.5230 4.2556 3 14 0.024745 *
rate:additive 1 0.7771 1.3385 3 14 0.301782
Residuals 16
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(f18, test=Wilks) # ANOVA table of Wilks' lambda
Df Wilks approx F num Df den Df Pr(F)
rate 1 0.3743 6.6880 3 12 0.006637 **
additive 1 0.5825 2.8671 3 12 0.080857 .
rate:additive 1 0.7012 1.7047 3 12 0.218966
Residuals 14
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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meet your needs.
hope this helps,
spencer graves
Naiara S. Pinto wrote:
Dear all,
I need to do a Manova but I have an unbalanced design. I have
morphological measurements similar to the iris dataset, but I don't have
the same number of measurements for all species. Does anyone know a
procedure to do Manova with this kind of input in R?
Thank you very much,
Naiara.
Naiara S. Pinto
Ecology, Evolution and Behavior
1 University Station A6700
Austin, TX, 78712
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