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copied!<p>The <code>tables</code> package makes everything in this except the p-values easy, and the p-values are doable. Here is a quick example:</p> <pre><code>> library(tables) > iris2 <- iris[ iris$Species != 'versicolor', ] > iris2$Species <- factor(iris2$Species) > tmp <- tabular( Petal.Width+Petal.Length + Sepal.Width+Sepal.Length ~ Species* (mean+sd), data=iris2 ) > > tmp.p <- sapply( names(iris2)[1:4], function(x) t.test( iris2[[x]] ~ iris2$Species )$p.value ) > > tmp setosa virginica mean sd mean sd Petal.Width 0.246 0.1054 2.026 0.2747 Petal.Length 1.462 0.1737 5.552 0.5519 Sepal.Width 3.428 0.3791 2.974 0.3225 Sepal.Length 5.006 0.3525 6.588 0.6359 > tmp2 <- cbind(tmp, tmp.p) > colnames(tmp2) <- c('Setosa Mean','Setosa SD', 'Virginica Mean','Virginica SD', + 'P-value') > tmp2 Setosa Mean Setosa SD Virginica Mean Virginica SD P-value Sepal.Length 0.246 0.1053856 2.026 0.2746501 3.966867e-25 Sepal.Width 1.462 0.173664 5.552 0.5518947 4.570771e-09 Petal.Length 3.428 0.3790644 2.974 0.3224966 9.269628e-50 Petal.Width 5.006 0.3524897 6.588 0.6358796 2.437136e-48 </code></pre> <p><strong>#### Edit ####</strong></p> <p>It looks like newer versions of tabular do more checks which makes the <code>cbind</code> approach not work any more (and this could be a good thing, since I am not sure that it was properly matching the values if the ordering was different). I did not find a simple way to still do this using <code>cbind</code> (though you could convert to a matrix, pad the rows for the headers, then <code>cbind</code>).</p> <p>Here is another approach that works, it is still a bit of a kludge since it hardcodes the species variable in the function (and the function would therefore have to be updated specifically for each table it is used in):</p> <pre><code>library(tables) iris2 <- iris[ iris$Species != 'versicolor', ] iris2$Species <- factor(iris2$Species) P.value <- function(x) t.test(x ~ iris2$Species)$p.value tmp <- tabular( Petal.Width+Petal.Length + Sepal.Width+Sepal.Length ~ Species* (mean+sd) + P.value, data=iris2 ) tmp </code></pre>

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