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st: ttest and log transformation


From   "Richard Harvey" <richardharvey2008@googlemail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: ttest and log transformation
Date   Sat, 27 Sep 2008 09:14:32 +0100

Hi all,

I hope I can ask a fairly basic stats question. I have a variable that
i need to compare across two groups.
the summary stats for the variable NAN  across the groups is as below.
The negative values are legitimate.

group   |            N             mean             p50           max
               min                skewness  kurtosis

group1 |           2537         -77535           5278       19051350
   -46844688         -11.23          311.1
group2 |           3031        -211373           4620        4609996
   -32617714         -11.18          185.6
 Total   |          5568        -150391           4958       19051350
    -46844688         -11.33          278.4

If a do a ttest on the log transformed data, is it appropriate to add
an arbitrary constraint to make the negative values positive?  Is the
ttest indeed any good for this data, or should I be looking at some
non parametric tests.

to make the numbers more manageble is divide by 1000,000 and the
summary stats look like this

group	          N		mean	p50	                max	           min	skewness	kurtosis
								
group1		2537		-.07753	.005278		19.05	-46.84	-11.23	311.1
group2		3031		-.2114	.00462		4.61	        -32.62	-11.18	185.6
Total		        5568		-.1504	.004958		19.05	-46.84	-11.33	278.4

Is it right to perform ttest on ln((NAN/1000000)+50) ? changing the
constant i add dosent seem to make a difference.

stats on ln((NAN/100000)+50) is as below

group	             N		mean	p50	                max	         min
	skewness	kurtosis
								
group1		2537		4.604	4.605		4.78	       3.973	            -17.21	527.4
group2		3031		4.603	4.605		4.65	         4.21	             12.74	242.9
Total		        5568 	4.604	4.605		4.78	       3.973             -15.94	469

There is still a large negative skewness coefficient.  To me this
looks like not a situation for a  ttest and I should be looking at
some non parametric test. Is that right?

The results from the ttest using the unpaired and unequal option,
using the untransformed and using ln((NAN/100000)+50) are as below

transformation               t                 p                       95% CI
None                          3.25            .0011
53205.45-214470.8
log(50+var)                 2.75            .0060
.000367 - .002185 ( I understand this has to be back transformed)

a ranksum test on the logtransformed NAN shows a z of 3.3999 with a p
of .0007.on the untransformed NAN it is 3.396 with p of .0007

so overall, there dosent seem to be any change in the conclusions,
what ever test I use. But is the ttest procedure appropriate?

You help is much appreciated.
-- 
thanks for your time
rich
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