R help - Aug 2008 - Major difference in the outcome between SPSS and R statistical programs

Dear collegues,
 
I have used R statistical program, package 'lmer', several times
already.
I never encountered major differences in the outcome between SPSS and R.
...untill my last analyses.
 
Would some know were the huge differences come from.
 
Thanks in advance, Ronald
 
In SPSS the Pearson correlation between variable 1 and variable 2 is 31%
p<0.001.

 

In SPSS binary logistic regression gives us an 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 OR=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?


	[[alternative HTML version deleted]]

The biggest problem is that SPSS cannot fit a generalized linear mixed
model but lmer does. So, why would you expect the GLM in SPSS and the
GLMM in lmer to match anyhow? 
> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of Draga, R.
> Sent: Friday, August 01, 2008 10:19 AM
> To: r-help at r-project.org
> Subject: [R] Major difference in the outcome between SPSS and 
> R statisticalprograms
> 
> Dear collegues,
>  
> I have used R statistical program, package 'lmer', several 
> times already.
> I never encountered major differences in the outcome between 
> SPSS and R.
> ...untill my last analyses.
>  
> Would some know were the huge differences come from.
>  
> Thanks in advance, Ronald
>  
> In SPSS the Pearson correlation between variable 1 and 
> variable 2 is 31% p<0.001.
> 
>  
> 
> In SPSS binary logistic regression gives us an 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 OR=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?
> 
> 
> 	[[alternative HTML version deleted]]
> 
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