# Re: [R] aov or t-test applied on all variables of a data.frame

From: Christoph Lehmann <christoph.lehmann_at_gmx.ch>
Date: Sat 12 Mar 2005 - 04:45:06 EST

many thanks for the sapply hint. How can I use sapply for a compact result of the aov computation, say I call

sapply(dd[-1], function(y, f) aov(y ~ f), f = dd\$V1)

aov gives the result in another form than t.test

thanks a lot

Peter Dalgaard wrote:
> Christoph Lehmann <christoph.lehmann@gmx.ch> writes:
>

>>Hi
>>I have a data.frame with say 10 continuous variables and one grouping
>>factor (say 3 levels)
>>
>>how can I easily (without loops) apply for each continous variable
>>e.g. an aov, with the grouping factor as my factor (or if the grouping
>>factor has 2 levels, eg. a t-test)
>>
>>thanks for a hint

>
> Generally something with lapply or sapply, e.g.
>
> lapply(dd[-1], function(y) t.test(y~dd\$V1))
>
> \$V2
>
> Welch Two Sample t-test
>
> data: y by dd\$V1
> t = 1.5465, df = 39.396, p-value = 0.13
> alternative hypothesis: true difference in means is not equal to 0
> 95 percent confidence interval:
> -0.02500802 0.18764439
> sample estimates:
> mean in group 1 mean in group 2
> 1.096818 1.015500
>
> ...etc, one for each of V2..V8
>
> or, in a more compact form
>
> sapply(dd[-1], function(y) t.test(y~dd\$V1))[1:3,]
>
> V2 V3 V4 V5 V6 V7
> statistic 1.546456 1.008719 0.08158578 -0.2456436 -0.872376 -1.405966
> parameter 39.39554 36.30778 39.70288 36.99061 36.99944 35.97947
> p.value 0.1299909 0.3197851 0.935386 0.807316 0.3886296 0.1683118
> V8
> statistic -0.6724112
> parameter 29.65156
> p.value 0.5065284
>
> or (this'll get the confidence intervals and estimates printed sensibly).
>
> sapply(dd[-1], function(y)unlist(t.test(y~dd\$V1)[1:5]))
>

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