| mcNemar {epibasix} | R Documentation |
This function performs elemenentary pair-matched analysis using McNemar's test and computing risk differences.
mcNemar(X, alpha= 0.05, force=FALSE, digits=3)
X |
A 2x2 matrix, with disease status (Yes/No) for the exposed individual in the columns and disease status (Yes/No) for the control individuals in the rows. Note that for a matched-pair analysis, each entry corresponds to a pair of subjects. |
alpha |
The desired Type I Error Rate for Hypothesis Tests and Confidence Intervals |
force |
Logical: McNemar's test is typically valid when the number of discordant pairs exceeds 30. The function may be forced to work, without regards to this concern with FORCE=TRUE. |
digits |
Number of Digits to round calculations |
McNemar's OR is computed as b/c. While standard errors are computed using a transformation. The risk difference is computed as (b-c)/n. Note that this technique can be used for cohort studies as well as matched trials.
X |
The original input matrix. |
ORMc |
McNemar's Odds Ratio |
ORMC.CIL |
Lower Confidence Limit for McNemar's OR |
ORMC.CIU |
Upper Confidence Limit for McNemar's OR |
rd |
Point Estimate of the risk difference |
rd.CIL |
Lower Confidence Limit for the risk difference |
rd.CIU |
Upper Confidence Limit for the risk difference |
XMc |
Value for McNemar's Chi-squared statistic |
XMc.p.Value |
P-value for the hypothesis test of no association. |
alpha |
The desired Type I Error Rate for Hypothesis Tests and Confidence Intervals |
digits |
Number of Digits to round calculations |
Michael Rotondi, mrotondi@uwo.ca
Szklo M and Nieto FJ. Epidemiology: Beyond the Basics, Jones and Bartlett: Boston, 2007.
## Not run: Data for matched-cohort study, comparing smokers to non-smokers for the presence of lung cancer. ## End(Not run) X <- cbind(c(15,5), c(19,61)); summary(mcNemar(X, alpha=0.05, force=TRUE));