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POSpearman correlation loop in R
 

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  1. POSpearman correlation loop in R
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    <p>A previous post explained how to do a Chi-squared loop in R on all your data-pairs: <a href="https://stackoverflow.com/questions/7382039/chi-square-analysis-using-for-loop-in-r">Chi Square Analysis using for loop in R</a>. I wanted to use this code to do the same thing for a Spearman correlation.</p> <p>I've already tried altering a few of the variables and I was able to calculate the pearson correlation variables using this code:</p> <pre><code>library(plyr) combos &lt;- combn(ncol(fullngodata),2) adply(combos, 2, function(x) { test &lt;- cor.test(fullngodata[, x[1]], fullngodata[, x[2]]) out &lt;- data.frame("Row" = colnames(fullngodata)[x[1]] , "Column" = colnames(fullngodata[x[2]]) , "cor" = round(test$statistic,3) , "df"= test$parameter , "p.value" = round(test$p.value, 3) ) return(out) }) </code></pre> <p>But since I work with data on an ordinal scale, I need to use the Spearman correlation.</p> <p>I thought I could get this data by just adding the method="spearman" command but this does not seem to work. If I use the code:</p> <pre><code>library(plyr) combos &lt;- combn(ncol(fullngodata),2) adply(combos, 2, function(x) { test &lt;- cor.test(fullngodata[, x[1]], fullngodata[, x[2]], method="spearman") out &lt;- data.frame("Row" = colnames(fullngodata)[x[1]] , "Column" = colnames(fullngodata[x[2]]) , "Chi.Square" = round(test$statistic,3) , "df"= test$parameter , "p.value" = round(test$p.value, 3) ) return(out) }) </code></pre> <p>I get the response:</p> <pre><code>Error in data.frame(Row = colnames(fullngodata)[x[1]], Column = colnames(fullngodata[x[2]]), : arguments imply differing number of rows: 1, 0 In addition: Warning message: In cor.test.default(fullngodata[, x[1]], fullngodata[, x[2]], method = "spearman") : Cannot compute exact p-values with ties </code></pre> <p>what am I doing wrong?</p>
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