Hi,
I am using R to fit statistical models to data were the observations are
means of the original data. R is used to calculate the mean before fitting
the model. My problem is: When R calculates the means using tapply, the
class of the means differs from the class of the original data, which gives
me trouble when I want to use the original data to calculate model
predictions. Here is a simple example that demonstrates the problem:
> data.in<-read.table('example.dat',header=TRUE)
>
> #Here are the data:
> data.in
location x y
1 A 17.2 28.46
2 A 91.7 143.33
3 A 93.6 148.05
4 B 95.8 150.28
5 B 54.9 89.49
6 B 51.1 82.51
7 C 53.9 88.46
8 C 40.3 63.62
9 C 38.5 64.46
>
> attach(data.in)
>
> #Calculate means by variable "location":
> data.mn<-data.frame(xm = tapply(x,location,mean), ym =
tapply(y,location,mean))
> detach(data.in)
>
> #Here are the means:
> data.mn
xm ym
A 67.50000 106.6133
B 67.26667 107.4267
C 44.23333 72.1800
>
> #Fit the model:
> mod1<-lm(ym ~ xm, data.mn)
>
> mod1
Call:
lm(formula = ym ~ xm, data = data.mn)
Coefficients:
(Intercept) xm
5.633 1.505
> #R will make "predictions" using the data.mn data frame:
> predict(mod1,newdata = data.mn)
A B C
107.19260 106.84153 72.18587
>
> #But, even if new variables are created in the original data
> #with names that match those names used in the regression:
> data.in$xm<-data.in$x
> data.in$ym<-data.in$y
> data.in
location x y xm ym
1 A 17.2 28.46 17.2 28.46
2 A 91.7 143.33 91.7 143.33
3 A 93.6 148.05 93.6 148.05
4 B 95.8 150.28 95.8 150.28
5 B 54.9 89.49 54.9 89.49
6 B 51.1 82.51 51.1 82.51
7 C 53.9 88.46 53.9 88.46
8 C 40.3 63.62 40.3 63.62
9 C 38.5 64.46 38.5 64.46
>
> #R will not use data.in to make predictions:
> predict(mod1,newdata = data.in)
Error: variable 'xm' was fitted with class "other" but class "numeric" was
supplied
>
> data.in$xm
[1] 17.2 91.7 93.6 95.8 54.9 51.1 53.9 40.3 38.5
> data.mn$xm
A B C
67.50000 67.26667 44.23333
>
Is there a way to make these variables have the same class? Or, is there
something other than "tapply" that will work better for this?
Thanks!
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