[R] cor(X) with P-Value

[Chuck Cleland]

   These functions are based on posts to either R-Help or S-News by 
Gabor Grothendieck and Bill Venables.

# pairwise sample size
# Gabor G - 11/23/2004 R-help List
pn <- function(X){crossprod(!is.na(X))}

cor.prob <- function(X){
# Correlations Below Main Diagonal
# Significance Tests with Pairwise Deletion
# Above Main Diagonal
# Believe part of this came from Bill Venables
pair.SampSize <- pn(X)
above1 <- row(pair.SampSize) < col(pair.SampSize)
pair.df <- pair.SampSize[above1] - 2
R <- cor(X, use="pair")
above2 <- row(R) < col(R)
r2 <- R[above2]^2
Fstat <- (r2 * pair.df)/(1 - r2)
R[above2] <- 1 - pf(Fstat, 1, pair.df)
R
}

mydata <- matrix(rnorm(1000), ncol=10)

cor.prob(mydata)

Worik Turei stanton wrote:
> Friends
> 
> I am new to R (and statistics) so am struggling a bit.
> 
> Briefly...
> 
> I am interested in getting the P-Value from cor(X) where X is a matrix.
> 
> I have found cor.test.
> 
> Verbosely...
> 
> I have 4 vectors and can generate the corellation matrix...
> 
> 
> 
>>cor(cbind(X1, X2, X3, X4))
> 
>             X1          X2           X3           X4
> X1  1.00000000 -0.06190365 -0.156972795  0.182547517
> X2 -0.06190365  1.00000000  0.264352860  0.146750844
> X3 -0.15697279  0.26435286  1.000000000 -0.006380052
> X4  0.18254752  0.14675084 -0.006380052  1.000000000
> 
> But I want the P-Values (gives me the significance I belive).
> 
> 
>>cor.test(X2, X3)
> 
> 
> 	Pearson's product-moment correlation
> 
> data:  X2 and X3
> t = 3.3346, df = 148, p-value = 0.001080
> alternative hypothesis: true correlation is not equal to 0
> 95 percent confidence interval:
>  0.1086963 0.4073565
> sample estimates:
>       cor
> 0.2643529
> 
> is very cool.  Just what I want.  But there is too much information for
> too little data.
> 
> What I would like to do is some thing like...
> 
> cor_with_p_test(cbind(X1, X2, X3, X4))
>      X1           X2              X3
> X1    1          -0.06190365      -0.1569728...
> P                0.4517           0.05507   ...
> 
> X2  -0.06190365  1                0.2643529 ...
> P   0.4517                        0.001080  ...
> :
> :
> 
> I think I could write a function for it if such a function does not exist
> if I could do...
> 
> 
>>CT23 <- cor.test(X2, X3)
>>CT23$P
> 
> 0.001080
> 
>>CT23$V
> 
> 0.2643529
> 
> But I do not know how.
> 
> cheers
> Worik
> 
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> 

-- 
Chuck Cleland, Ph.D.
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