|Date: ||Thu, 30 Jun 2005 08:46:16 -0400|
|Sender: ||"SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>|
|Subject: ||Re: McNemar Test and Study Design|
|Content-type: ||text/plain; charset=US-ASCII|
This sounds like a bad way to measure the impact of your intervention
because you are throwing out a bunch of information. If 19% of your
respondents gave you a top-box response to the Likert scale, then I would
guess your measure of central tendency is well behaved. If strongly agree
= 5 and strongly disagree = 1 and your pre treatment mean is 3 and your
post-treatment mean is 3.7, then I think something happened regardless of
which 19% answered strongly agree.
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.UGA.EDU> McNemar Test and Study Design
Please respond to
We've been asked by a reviewer to provide further explanations about
why we chose to use a McNemar test to determine whether the marginal
proportions in a 2X2 table were statistically different, and I am hoping
some on this list may be able to provide some guidance.
The study employed a pre/post design where patients were surveyed at
intake and then again after their consultations. So, the same people
were surveyed twice, once at intake and again after the consultation
(which is in effect the "treatment" we're studying). As I understand
it, the McNemar test is appropriate for this design.
The response alternatives to the survey questions used a 5 point Likert
format, with responses ranging from Strongly Disagree to Strongly Agree.
So, to use the McNemar, each response alternative to each question was
transformed into a binary variable, such that a "Strongly Agree" answer
to Q4 on the pretest meant that the variable Q4pre_e = 1, while Q4pre_a
through Q4pre_d all were assigned a zero. Likewise, on the post test,
if the respondent answered "Neither" then Q4post_c = 1, while the
remaining 4 "post" variables were assigned a value of 0. McNemar tests
were executed on all 5 pairs of pre/post variables; none of them were
The reviewer raised the question, "although roughly 1 in 5 patients
answered "Strongly Agree" both before and after the consultation, were
they the same individuals?" The immediate answer is, well, yes, as is
defined in the design of the study. But if the reviewer is actually
asking whether the 19% answering "Strongly Agree" at intake are the same
individuals composing the 21% answering "Strongly Agree" on the
post-test, I am left wondering whether this is a moot concern, or
whether this may confound the results of the McNemar. Can anyone help
Loyola University Medical Center
"Everything that can be counted isn't worth counting,
and everything that is worth counting isn't always countable."