Dear colleagues,
I know SPSS can not compute linear mixed models. I used 'R' before for
computing multivariate analyses. But, I never encountered such a major
difference in outcome between SPSS and 'R':
In SPSS the Pearson correlation between variable 1 and variable 2 is 31%
p<0.001.
In SPSS binary logistic regression gives us an Odds Ratio (OR)=4.9 (95%
CI 2.7-9.0), p<0.001, n=338.
OR lower upper
gender 1,120 0,565 2,221
age 0,985 0,956 1,015
variable 2 4,937 2,698 9,032
In R multilevel logistic regression using statistical package 'lmer'
gives us an Odds Ratio=10.2 (95% CI 6.3-14), p=0.24, n=338, groups:
group 1, 98; group 2 84.
OR lower upper
gender 2,295 -2,840 7,430
age 0,003 -70,047 70,054
variable 2 10,176 6,295 14,056
The crosstabs gives us:
variable A
Var B 0 1
0 156 108
1 17 57
Would somebody know how it is possible that in SPSS we get p<0.001 and
in R we get p=0.24?
And, in 'R' the 95% CI of the Odds Ratio is 6.2-14.1. Why is the
p-value=0.24?
Thanks,
Ronald
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