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Date:         Tue, 3 Apr 2007 15:06:17 -0500
Reply-To:     "Swank, Paul R" <>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         "Swank, Paul R" <>
Subject:      Re: McNemar test
In-Reply-To:  <>
Content-Type: text/plain; charset="us-ascii"

I agree that McNemar's test is like a paired (or dependent samples) t test but it works on a 2 by 2 table where the table represents paired frequencies. For example, if 100 people report whether or not they agree or disagree with two political statements, then the results can be reported as a 2 by 2 table:

1st statement 2nd statement agree disagree total agree 30 10 40

disagree 20 40 60

total 50 50 100

The typical chi-squared test for such a table is a measure of association between the statements Indicatig a significant relation (chi-square(df=1, n=100) = 16.67; p < .01). The McNemar test is concerned with the equality of the marginal proportions (p(1.) = P(.1). That is, is the proportion who agree with the first statement (40%) different from the proportion who agree with the second statement (50%)? This is equivalent to the test of symmetry for the table (p(12) = p(21) The large sample test statistic is chi-square(1) = (10 - 20)**2 / (10+20) = 3.33; p > .05.

Paul R. Swank, Ph.D. Professor Director of Reseach Children's Learning Institute University of Texas Health Science Center-Houston

-----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Burleson,Joseph A. Sent: Monday, April 02, 2007 12:27 PM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Re: McNemar test


The McNemar test does not test the difference between the two proportions in a 2 X 2 chi-square. It is used to assess change across time (or some other within-subjects variable): does the change from 0 to 1 differ significantly from the change from 1 to 0, for example (it ignores the frequencies of subjects who go from 0 to 0 and from 1 to 1).

Hence, it is like a "paired t-test" for dichotomous data.

See Siegel, S. (1956). Non parametric statistics for the behavioral sciences. New York: McGraw-Hill. p. 63-67.

Joe Burleson -----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Lou Sent: Monday, April 02, 2007 11:18 AM To: SPSSX-L@LISTSERV.UGA.EDU Subject: McNemar test

Dear all,

Could someone please advise on the best way to report the results of a McNemar test. If I state beforehand that I am using McNemar, do I simply label the test statistic as being 'chi-square'?

For example, I have compared the proportions 82.59% and 76.62%. This gives a value of the McNemar statistic of 172.567 with p < 0.001 and N = 7920. I have calculated a 95% confidence interval for the difference of (5.09%, 6.85%).

I would like to report this (and similar) information in the most accurate and way possible. Suggestions please?

Many thanks,


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