On 11/11/2013 1:01 PM, Michael Britt 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



Hi Michael:

Tabachnick and Fidell (2007, 5th ed., pp. 86-90) suggest the following transformation for negatively-skewed data.

First, you should create a new variable that is a reflection of the original data:

NewX = K - OldX  ;where K = your max score + 1.

Then try a square root or a log transform of NewX and see which transform produces the smallest skew score.

Finally, remember that the reflection reverses the direction of your scale. A 10 indicates low satisfaction.


Ken


------------------------------------------------------------------------
Kenneth M. Steele, Ph. D.                        [email protected]
Professor
Department of Psychology                 http://www.psych.appstate.edu
Appalachian State University
Boone, NC 28608
USA
------------------------------------------------------------------------

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