[R] Comparing two pairs of non-normal datasets in R?
Spencer Graves
spencer.graves at pdf.com
Tue Jun 8 21:34:36 CEST 2004
It looks like "ks.test" might help, but it seems to me you need to
make parsimonious models of the change in distributions, so you estimate
a few parameters for the distributions of each of your 4 data sets with
standard errors for all the parameters you estimate. Then you can test
if the change in the estimated parameters in going from A1 -> A2 exceeds
the change going from C1 -> C2 using z scores or t tests of the
differences in the parameter estimates -- or chi-squares / F's, etc., if
you want to do multiple dimensions all at once.
hope this helps. spencer graves
Peter Sebastian Masny wrote:
>On Tuesday 08 June 2004 10:43 am, you wrote:
>
>
>>If I understand you correctly, you have two set of ***paired***
>>data, one set from the A population, and one from the C population.
>>
>>Form the pairwise differences:
>>
>> A.diff <- A1 - A2
>> C.diff <- C1 - C2
>>
>>
>
>Alas, they are not paired. A1 and A2 are samples from the same population,
>but of different members. Also, the number of measurements is different for
>each dataset.
>
>
>
>>Boxplots and histograms of A.diff and C.diff will tell you
>>(much more than a test ever would) what's ***really*** going on.
>>
>>
>
>The boxplots I have clearly show the difference, but I need a p value to go
>with it.
>
>Here are the boxplots if that helps:
>http://www.ps.masny.dk/guests/misc/A1.png
>http://www.ps.masny.dk/guests/misc/A2.png
>http://www.ps.masny.dk/guests/misc/C1.png
>http://www.ps.masny.dk/guests/misc/C2.png
>
>
>
>>P.S. BTW --- you say that your data are continuous, but that their
>>distributions are ``more like a Poisson''. The Poisson distribution
>>is DISCRETE!!!
>>
>>
>
>Hence the "like". The data is indeed continuous, but a distribution graph
>increases towards one extreme...
>
>Visually, the results are convincing, but I really need a test of
>significance.
>
>
>
>Thank you very much for the help,
>
>Peter
>
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