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

[Christoph Lehmann]

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 at 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]))
>