Thanks for all these suggestions.  I've been thinking of trying all or most of 
them. I assume that I would get slightly different results, so let me ask this: 
what criteria would you use to determine which transformation gave the best 
result?  Would it be the one with the least amount of skew/most normal in 
distribution?

 
Michael A. Britt, Ph.D.
[email protected]
http://www.ThePsychFiles.com
Twitter: @mbritt

On Nov 11, 2013, at 7:04 PM, Jim Clark <[email protected]> wrote:

> Hi
> 
> People have been noting various transformations, depending on reversing or 
> not the original.  In essence many common transformations can be 
> conceptualized as the original scores raised to various powers, with the 
> powers being greater than or less than 1.
> 
> x^-1 = reciprocal 1/x
> x^~0 = logarithmic
> x^.5 = square root
> x^1 = original
> x^2 = ...
> 
> I'm mostly used to thinking of these in terms of various non-linear 
> relationships (powers < 1 compress upper end, powers > 1 expand upper end), 
> but some of these will increase skewness and others will decrease it, 
> depending on the direction of skew. Possible to experiment with them to 
> observe effect.
> 
> Perhaps also worth plotting some of the relationships you are interested in?
> 
> Take care
> Jim
> 
> Jim Clark
> Professor & Chair of Psychology
> 204-786-9757
> 4L41A
> 
> -----Original Message-----
> From: Christopher Green [mailto:[email protected]] 
> Sent: Monday, November 11, 2013 5:31 PM
> To: Teaching in the Psychological Sciences (TIPS)
> Subject: Re: [tips] What to do with skewed data
> 
> Michael, 
> 
> There are couple of standard ways to transform skewed data. Invert the data 
> (subtract each datum from one greater than the highest value) so that the 
> skew is positive. Then, Depending of the strength of the skew, do a square 
> root or logarithmic transformation. Alternatively, don't invert it and take 
> the reciprocal (1/x) of each datum).
> 
> Chris
> .......
> Christopher D Green
> Department of Psychology
> York University
> Toronto, ON M6C 1G4
> 
> [email protected]
> http://www.yorku.ca/christo
> 
>> On Nov 11, 2013, at 1:01 PM, Michael Britt <[email protected]> wrote:
>> 
>> I did a survey which asked respondents how satisfied they are in their 
>> current (romantic) relationship on a 1=10 point scale (where 10="very 
>> satisfied).  While there was some variation, not surprisingly, the results 
>> are strongly negatively skewed.  That makes sense - most people are probably 
>> satisfied with their relationships or they would leave the other person (or 
>> there's some form of cognitive dissonance going on, but that's not my 
>> question.
>> 
>> No matter how big the sample size (mine was 160 respondents) I assume you'll 
>> always get a skewed distribution on a question like this so wouldn't I be 
>> breaking the normalization assumption if I were to do correlations using 
>> these results?   I assume I could either do:  a) do some kind of 
>> transformation - but I've never done one before so I’m not familiar with it, 
>> or b) recode the data into 3 categories (perhaps 1-5 is low satisfaction, 
>> 6-7 is moderate and 8-10 is high) and do a chi-squre instead of a 
>> correlation.
>> 
>> Any thoughts?  Appreciate it.
>> 
>> Michael
>> 
>> Michael A. Britt, Ph.D.
>> [email protected]
>> http://www.ThePsychFiles.com
>> Twitter: @mbritt
>> 
>> 
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