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