Thanjavur Bragadeesh [EMAIL PROTECTED] writes:
Hi,
I am trying to run an analysis of variance using R.
in my data table x is a continuous variable lengthof 200 and p is a
categorical variable also of length 200 and p is anyone of three categories
1,2 or ,3.
if I run
summary(aov(x~p,data=test))
I get
Response: x
Df Sum Sq Mean Sq F valuePr(F)
p 1 3174.7 3174.7 42.749 5.175e-10 ***
Residuals 198 14704.274.3
If you get 1 DF for a variable with three different values, then it is
not a categorical variable from R's point of view, but a quantitative
one. So you need x~factor(p) here like you have below. Or convert p
to a factor before the analysis.
and if I run
summary(aov(x~as.factor(p), data=test)) # I get
Response: x
Df Sum Sq Mean Sq F value Pr(F)
as.factor(p) 2 3175.7 1587.8 21.275 4.31e-09 ***
Residuals 197 14703.274.6
Can anyone kindly explain the difference. How will it affect -correct way to
run - if it is a two-way anova where I have a second categorical variable
sex - male or female.
Many Thanks
Yours sincerely,
Bragadeesh
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