Created
May 12, 2011 12:26
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Function for calculating pairwise correlations between b*c columns of data in a data frame
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# a = data frame | |
# b = list of variables in x | |
# c = list of variables in y | |
# method_ = one of pearson, spearman, kendall (or their abbreviations) | |
# output is a data frame with as many columns as b * c | |
GetCorrs <- function(a, b, c, method_) { | |
dfout_ <- list() | |
names <- list() | |
names_ <- list() | |
for(i in 1:length(b)) { | |
dfout <- data.frame(r = rep(NA, length(c)), P = rep(NA, length(c))) | |
for(j in 1:length(c)) { | |
rout <- cor.test(a[, b[i]], a[, c[j]], alternative = "two.sided", method = method_) | |
dfout[j, ] <- c(as.numeric(rout[[4]]), as.numeric(rout[[3]])) | |
names[[j]] <- paste(names(a)[b[i]], names(a)[c[j]], sep="_") | |
} | |
dfout_[[i]] <- dfout | |
names_[[i]] <- names | |
} | |
dfout_df <- do.call(rbind, dfout_) | |
dfout_df$traits <- as.vector(sapply(names_, function(x) laply(x, identity))) | |
return(dfout_df) | |
} |
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