McNemar's Test for Correlated Proportions in the Marginals of a 2x2 Contingency Table
Individual Subjects Assessed with Respect to Two Dichotomous Variables. Suppose that 100 subjects are each assessed with respect to two dichotomous categorical variables,
Subject's Measure
on Variable B
1
0
Totals
Subject's Measure
on Variable A
1
25
5
30
0
15
55
70
Totals
40
60
100
A and B. If the temporal sequence of the two measures is relevant,Variable A can be defined as the "before" measure andVariable B as the "after" measure. The results are coded as "1" for those subjects that display the property defined by the variable in question and as "0" for those that do not display that property. The marginal proportions in this example are:T
pA = 30/100 = .30 andTT
pB = 40/100 = .40T
That is: 30% of the subjects display the characteristic defined byVariable A and 40% display the characteristic defined byVariable B.
Matched Pairs of Subjects Assessed with Respect to One Dichotomous Variable. Suppose that 100 matched pairs of subjects are each assessed with respect to a single categorical variable. One member of each pair is the "A" member and the other is the "B" member. Alternatively, in the language of clinical research, one member of each pair is the "case" and the other is the "control." In the present example, 25 of the matched pairs have both the A and the B member showing the characteristic in question; 5 have the A member but not the B member showing the characteristic; and
Measure for
Pair Member B
(Control)
1
0
Totals
Measure for
Pair Member A
(Case)
1
25
5
30
0
15
55
70
Totals
40
60
100
so on. Here again, the marginal proportions are:T
pA = 30/100 = .30 andTT
pB = 40/100 = .40T
That is: the characteristic in question is displayed by 30% of the A (or Case) members and by 40% of the B (or Control) members.
| General Structure | B| 1 | 0 | Totals | A | 1 | a | b | a+b | 0 | c | d | c+d | Totals | a+c | b+d | pA = (a+b)/NT | pB = (a+c)/N | ||||||||
|
The basic concepts and computational details of
binomial probabilities are described in Chapters 5 & 6 of Concepts and Applications of Inferential Statistics. |
B| 1 | 0 | Totals | A
| 1 | | ||||
| Proportions | Difference (Unsigned) | |
| pA |
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