Ng Stanley wrote:
> Hi,
>
> Given
>
> test <- matrix(c(1, 1,2,2), 2,2)
> t <- apply(test, 1, t.test)
>
> How can I obtain a table of p-values, confidence interval etc, instead of
A quick hack would be:
m <- t(sapply(t, function(x) c(x[["p.value"]], x[["conf.int"]])))
colnames(m) <- c("p", "lwr", "upr")
m
>
> [[1]]
>
> One Sample t-test
>
> data: newX[, i]
> t = 3, df = 1, p-value = 0.2048
> alternative hypothesis: true mean is not equal to 0
> 95 percent confidence interval:
> -4.853102 7.853102
> sample estimates:
> mean of x
> 1.5
>
>
> [[2]]
>
> One Sample t-test
>
> data: newX[, i]
> t = 3, df = 1, p-value = 0.2048
> alternative hypothesis: true mean is not equal to 0
> 95 percent confidence interval:
> -4.853102 7.853102
> sample estimates:
> mean of x
> 1.5
>
> [[alternative HTML version deleted]]
>
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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