a question about "by" and "ddply"

On May 29, 2012, at 6:32 PM, jacaranda tree wrote:

Hi all,
I have a data set (df, n=10 for the sake of simplicity here) where I have
two continuous variables (age and weight) and I also have a grouping
variable (group, with two levels). I want to run correlations for each group
separately (kind of similar to "split file" in SPSS). I've been
experimenting with different functions, and I was able to do this correctly
using ddply function, but output is a little bit difficult to read when I do
the cor.test to get all the data with p values, df, and pearson r (see
below). I also tried to do it with by function. Although, with by, it shows
the data for two groups separately, it seems like it calculates the same r
for both groups. Here is my code for both ddply and by, and the output as
well. I was wondering if there is a way to display the output better with
ddply or run the correlations correctly for each group using by.
Thanks in advance,

I would have imagined something along the lines of

lapply( split( df, df$group, function(x) cor.test(x[["age"]], x[["weight")]
)

... but without an example it's only a guess.

--
David

1.with ?"ddply"
r<-ddply(df, .(group), summarise, "corr" = cor.test(age, weight, method =
"pearson"))

Output:
? Group ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? corr
1 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?Inf
2 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?3
3 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?0
4 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?1
5 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?0
6 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ? ?two.sided
7 ? ? ?1 Pearson's product-moment correlation
8 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? age and weight
9 ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 1, 1
10 ? ? 2 ? ? ? ? ? ? ? ? ? ? ? ? ? ? 9.722211
11 ? ? 2 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?3
12 ? ? 2 ? ? ? ? ? ? ? ? ? ? ? ? ?0.002311412
13 ? ? 2 ? ? ? ? ? ? ? ? ? ? ? ? ? ?0.9844986
14 ? ? 2 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?0
15 ? ? 2 ? ? ? ? ? ? ? ? ? ? ? ? ? ?two.sided
16 ? ? 2 Pearson's product-moment correlation
17 ? ? 2 ? ? ? ? ? ? ? ? ? ? ? age and weight
18 ? ? 2 ? ? ? ? ? ? ? ? 0.7779640, 0.9990233

2. with "by"
r <- by(df, group, FUN = function(x) cor.test(age, weight, method =
"pearson"))

Output:
Group: 1

? ? ? ?Pearson's product-moment correlation

data: ?age and weight
t = 6.4475, df = 8, p-value = 0.0001988
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
?0.6757758 0.9802100
sample estimates:
? ? ?cor
0.9157592

------------------------------------------------------------
Group: 2

? ? ? ?Pearson's product-moment correlation

data: ?age and weight
t = 6.4475, df = 8, p-value = 0.0001988
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
?0.6757758 0.9802100
sample estimates:
? ? ?cor
0.9157592
? ? ? ?[[alternative HTML version deleted]]