R aov Function


aov() function is for analysis of variance (ANOVA).

aov(formula, data=NULL, ...)

formula: a formula specifying the model
data: the data frame containing the variables specified in the formula

Following is a csv file example, we will do ANOVA analysis:

(Download the data file)

Let first read in the data from the file:
>x <- read.csv("anova.csv",header=T,sep="\t")

One way ANOVA analysis:
> a = aov(Expression~Subtype, data=x)
> summary(a)
             Df Sum Sq Mean Sq F value Pr(>F)  
Subtype       2   4.75  2.3769   3.991 0.0196 *
Residuals   278 165.59  0.5956                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
Please pay attention to the formula format, dependant variance "Expression" is in front of the independant variance "Subtype".

Report the means and the number of subjects:
>print(model.tables(a,"means"),digits=2)
Tables of means
Grand mean
           
-0.3053381 

 Subtype 
         A     B     C
     -0.18 -0.39 -0.49
rep 143.00 75.00 63.00


Two way ANOVA analysis:
> a = aov(Expression~Subtype*Age, data=x)
> summary(a)
             Df Sum Sq Mean Sq F value Pr(>F)  
Subtype       2   4.75   2.377   3.975 0.0199 *
Age           1   0.09   0.095   0.159 0.6905  
Subtype:Age   2   1.04   0.518   0.866 0.4217  
Residuals   275 164.46   0.598                 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
Here, dependant variance is "Expression", "Subtype" and "Age" are independant variances.

Report the means and the number of subjects:
>print(model.tables(a,"means"),digits=2)
Tables of means
Grand mean
           
-0.3053381 

 Gender 
         f      m
     -0.39  -0.22
rep 135.00 146.00

 Subtype 
         A     B     C
     -0.22 -0.36 -0.44
rep 143.00 75.00 63.00

 Gender:Subtype 
      Subtype
Gender A   B   C  
   f     0   0  -1
   rep  40  49  46
   m     0  -1   0
   rep 103  26  17