Re: Percent Change Crosstabs

Posted by Rich Ulrich on May 29, 2013; 7:45pm
URL: http://spssx-discussion.165.s1.nabble.com/Percent-Change-Crosstabs-tp5720440p5720469.html

This whole thread seems far too complicated, for discussing
a 2x2 table.  You have a table, you have a test, and you can
invert the p-level of the simple test, as needed. Thus, you may
describe a CI  in whatever contrastive terms that you choose.

The fact you have to face is that "relative risk" tends to be a really
crappy contrast to generalize from, since  it is so strongly affected
by base-rates.  That is why it seldom is to be preferred over the Odds
Ratio.  But its lousy generality does not justify using a lousy computation
to describe its "significance" for a particular table.

If you get opposite results from looking at "relative risk" when you
swap 0 and 1 ... as someone did, earlier in this thread ... that outcome
should be used to disqualify the method that gives those results.
There is *still* only one basic hypothesis about the differences. 

The test of the basic hypothesis?
For moderately large N in all cells, Fisher's Exact Test and both the
corrected and uncorrected Pearson chi-squared all give near-identical
results.  For 2x2, I think that the Likelihood Chi squared is also the same.
If you have tiny cells or extreme proportions, you can get some
different results from different ways to approximate computations
or corrections.  Continuity correction?  Unequal variances, and use d.f.?

--
Rich Ulrich

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Date: Wed, 29 May 2013 12:31:40 -0400
From: [hidden email]
Subject: Re: Percent Change Crosstabs
To: [hidden email]

John,

 

You certainly can. I thought the OP was interested in statistical testing/confidence intervals. 

 

With that said, one can use the approach outlined by Bruce or myself to test if the absolute difference is significantly different from zero.  

 

However, if one is interested in a statistical test regarding percent change in risk, then I would argue that it would be more appropriate to test whether the relative risk (RR) is significantly different from 1.0. With the model parameterized correctly, one could directly obtain the RR confidence limits, which could be converted to % change in risk.

 

Best,

 

Ryan

On Wed, May 29, 2013 at 12:22 PM, John F Hall <[hidden email]> wrote:

Forgive a naive question, but with a 2 x 2 table why can’t you simply calculate epsilon (% diff) by hand?  This technique is called elaboration,  See: M Rosenberg,  The Logic of Survey Analysis (Basic Books, 1968)

 

 

John F Hall (Mr)

[Retired academic survey researcher]

 

Email:   [hidden email] 

Website: www.surveyresearch.weebly.com

SPSS start page:  www.surveyresearch.weebly.com/spss-without-tears.html

  

  

 

 

 

 

 

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of DKUKEC
Sent: 29 May 2013 14:53
To: [hidden email]
Subject: Re: Percent Change Crosstabs

 

Thank you Ryan & Bruce, Very much appreciate your replies and suggested syntax. I am looking for the following computations... for example: % Difference in recidivism rate = Treatment Recidivism % - Control Recidivism %. % Change in the recidivism = Difference % / Control Recidivism %. *************************************************************************** 2X2 CROSSTAB EXAMPLE Recidivist Non-Recidivist Total Treatment 816 1133 1949 Control 936 1013 1949 Row % Row % Row % Treatment 41.9% 58.1% 100.0% Control 48.0% 52.0% 100.0% ****** Would like to compute %************************* Difference -6.1% % Change -12.7% ***************************************************** Sincerely, Damir

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