Classic solution: use a rank transformation -- that is, use the
Spearman coefficient rather than the Pearson coefficient.
Alternative -- use Kendall tau
Another alternative -- do as Ken suggests, but need not reflect first,
just use square instead of square root (you can alter the strength of this
transformation by changing the exponent) or use exponential transformation
instead of log transformation.
Modern solution -- bootstrap it. David Howell has, on his website,
free resampling software for simple designs.
Cheers,
Karl W.
-----Original Message-----
From: Michael Britt [mailto:mich...@thepsychfiles.com]
Sent: Monday, November 11, 2013 1:01 PM
To: Teaching in the Psychological Sciences (TIPS)
Subject: [tips] What to do with skewed data
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.
mich...@thepsychfiles.com
http://www.ThePsychFiles.com
Twitter: @mbritt
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