Dear all,
I need to perform a two-way unbalanced ANOVA on my data set. The unbalancing
is due to missing values (NA) for some subjects. My data set concerns the
evaluation of 4 different prototypes tested by subjects three times and it
is organized as follows (column by column):
number of observation number of subjects type of prototype replication
score
replication is from 1 to 3 and score is the score that each subject gave for
each replication for each prototype.
I know that I cannot use aov(), so I used the function lm in the following
way:
a.lm<-lm(Score~(Prototype*Replication),na.action=na.omit,data=a.ex)
Anova(a.lm,type=c("II"))
the output was:
Anova Table (Type II tests)
Response: Score
Sum Sq Df F value Pr(>F)
Prototype 216.61 3 10.1598 1.816e-06 ***
Replication 49.24 1 6.9287 0.008803 **
Prototype:Replication 2.91 3 0.1366 0.938133
Residuals 2906.69 409
I used these in the right way? I extensively read previous post on Anova(),
lm () and so on, but I am confused.
Then, I would like to verify the normality of residuals and the homogeneity
of variance. My idea was to apply the shapiro test on the residuals and the
bartlett or the levene test.
Please, someone can provide me with some suggestion?
thank you for your attention
netrunner
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