McNemar test in R & SPSS
Bob Green wrote:
Hello, I am hoping someone can clarify why I might obtain a quite different value in R & SPSS for a McNemar test I ran. Firstly, here is the R syntax & output R OUTPUT
> mctest <- as.table(matrix(c(128,29,331,430),
+ ncol =2, dimnames = list(group=c("preMHT","postMHT"),
+ assault=c("yes","no"))))
> mctest
assault group yes no preMHT 128 331 postMHT 29 430
> mcnemar.test(mctest,correct=F)
McNemar's Chi-squared test
data: mctest
McNemar's chi-squared = 253.3444, df = 1, p-value < 2.2e-16
SPSS OUTPUT
The same data was inputted in SPSS. Regarding the first table SPSS
generated - it lists the number of cases in each combination of categories.
The diagonal contains the number of cases with the same response on both
variables, while the off diagonal contains cases that have different
responses on the 2 variables. The overall chisquare value is much lower
than the value obtained using R, though still significant.
pre02 & post02
pre02 post02
0 1
0 311 20
1 119 9
Test Statistics(b)
pre02 & post02
N 459
Chi-Square(a) 69.094
Asymp. Sig. .000
a Continuity Corrected
b McNemar Test
Any assistance is much appreciated,
Well, you can't expect R to give the correct result if you feed it the wrong matrix, can you?
d <- read.table(stdin())
0: 0 1 1: 0 311 20 2: 1 119 9 3:
d
X0 X1 0 311 20 1 119 9
mcnemar.test(as.matrix(d),correct=F)
McNemar's Chi-squared test data: as.matrix(d) McNemar's chi-squared = 70.5108, df = 1, p-value < 2.2e-16
mcnemar.test(as.matrix(d),correct=T)
McNemar's Chi-squared test with continuity correction data: as.matrix(d) McNemar's chi-squared = 69.0935, df = 1, p-value < 2.2e-16
Bob Green
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