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McNemar test on paired proportions

Description

The McNemar test is a test on a 2x2 classification table when the two classification factors are dependent, or when you want to test the difference between paired proportions, e.g. in studies in which patients serve as their own control, or in studies with "before and after" design.

In the example used by Bland (2000) 1319 schoolchildren were questioned on the prevalence of symptoms of severe cold at the age of 12 and again at the age of 14 years. At age 12, 356 (27%) children were reported to have severe colds in the past 12 months compared to 468 (35.5%) at age 14.

Was there a significant increase of the prevalence of severe cold?

The data are entered as follows in the dialog box:

 PositiveNegative
Positive212144
Negative256707

 

Results

The program gives the difference between the proportions (expressed as a percentage) with 95% confidence interval. When the (two-sided) P-value is less than the conventional 0.05, the conclusion is that there is a significant difference between the two proportions. In the example, the difference between the prevalence at age 12 and age 14 is 8.49% with 95% CI from 5.5% to 11.4%, and is highly significant (P<0.0001).

In the Comment input field you can enter a comment or conclusion that will be included on the printed report.

Note

The two-sided P-value is based on the cumulative binomial distribution.

The 95% confidence interval is calculated according to Sheskin, 2011.

For the same test on raw data (spreadsheet data) see the McNemar test in the Statistics menu.

Literature

  • Altman DG (1991) Practical statistics for medical research. London: Chapman and Hall.
  • Sheskin DJ (2011) Handbook of parametric and nonparametric statistical procedures. 5th ed. Boca Raton: Chapman & Hall /CRC.

Link

Go to McNemar test on paired proportions.