[R] Comparing two pairs of non-normal datasets in R?

[Spencer Graves]

      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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