Hi Luigi,

Thanks for sending the data in reproducible format.   Perhaps something
like this?

aggregate(my.data[,3], list(my.data[,2]), FUN = function(x) t.test(x)$
conf.int[1:2])

#Group.1           x.1           x.2
#1 Unstimulated  5.296492e+02  2.410510e+03
#2        ESAT6  9.105338e+00  4.078439e+03
#3        CFP10  7.926311e+02  1.142267e+04
#4      Rv3615c  2.292658e+02  3.049608e+03
#5       Rv2654  7.396946e+02  7.311250e+03
#6       Rv3879 -6.603980e+02  5.777805e+03
#7       Rv3873  1.020891e+02  6.975473e+03
#8          PHA -2.236601e+05  6.508877e+05

HTH,
Jorge.-


On Tue, Mar 25, 2014 at 7:51 PM, Luigi Marongiu <marongiu.luigi@gmail.com>wrote:

> Dear all,
> I would like to calculate the confidence intervals on aggregate data. I
> know how to do this using the t test, but it did not work together with the
> aggregate function.
> Is there a function that can be applied to the aggregate function to obtain
> the (95%) confidence intervals, rather than applying a calculation?
> Best regards,
> Luigi
>
>
>  my.data<-structure(list(
>    column_1 = 1:120,
>    column_2 = structure(c(
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8,
>  1,2,3,4,5,6,7,8), .Label = c("Unstimulated", "ESAT6", "CFP10", "Rv3615c",
> "Rv2654", "Rv3879", "Rv3873", "PHA"), class = "factor"),
>      column_3 = c(
>  192.0519108,183.6403531,53.46798757
> ,83.60638077,69.60749873,159.4706861,256.8765622,499.2899303,
>  2170.799076,1411.349719,2759.472348,2098.973397,2164.739515
> ,1288.676574,1611.486543,6205.229575,
>  870.7424981
>
> ,465.9967135,191.8962375,864.0937485,2962.693675,1289.259137,2418.651212,7345.712517,
>  0,168.1198893,674.4342961,101.1575401,47.81596237,0,0,1420.793922,
>  142.6871331,5.466468742,291.9564635,80.73914133
> ,73.02239621,64.47806871,144.3543635,3167.959757,
>  3164.748333
>
> ,1092.634557,28733.20269,1207.87783,729.6090973,151.8706088,241.2466141,9600.963594,
>  1411.718287,12569.96285,1143.254476,6317.378481
> ,16542.27718,79.68025792,1958.495138,7224.503437,
>  208.4382941
>
> ,69.48609769,656.691151,0.499017582,7114.910926,187.6296174,41.73980805,8930.784541,
>  4.276752185,0.432300363,60.89228665
> ,1.103924786,0.490686366,1.812993239,7.264531581,1518.610307,
>  2172.051528
>
> ,595.8513744,17141.84336,589.6565971,1340.287628,117.350942,593.7034054,24043.61463,
>  0,81.83292179
> ,1539.864321,36.41722958,8.385131047,161.7647376,65.21615696,7265.573875,
>  97.84753179
>
> ,154.051827,0.613835842,10.06138851,45.04879285,176.8284258,18795.75462,3067686.769,
>
>  5780.34957,944.2200834,2398.235596,1083.393165,2541.714557,1251.670895,1547.178549,1792.679176,
>
>  3067.988416,8117.210173,23676.02226,8251.937547,17360.80494,18563.61561,16941.865,31453.96708,
>
>  2767.493803,4796.33016,12292.93705,3864.657567,9380.673835,14886.44683,8457.88646,26050.47191)),
> .Names = c("row", "stimulation", "copy"), row.names = c(NA, -120L),
>  class = "data.frame")
> attach(my.data)
>
>
> # ??? question: confidence intervals for each variable ???
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> 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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