Different results for linear regression in SPSS vs JASP

Sanne

Hi all,

Are you familiar with the fact that spss gives different results for regression than regression in JASP?
I did Bayes regression and found good results, and when checking with 'normal' regression in JASP I found similar results. However, the same analysis in SPSS resulted in non-sign findings and no correlation. The opposite of what was found using JASP.

Do you have an explanation? Of course I hope JASP outcomes are correct

Thanks!
Sanne

EJ

Hi Sanne,

We use code from R packages, and most of the time SPSS is wrong and R is right, but who knows, this may be an exception. Can you provide more specifics so we can look into it?

Cheers,
E.J.

susanneschweizer

Hi E.J. and Sanne,

I have encountered the same discrepancy (example below).
JASP does indeed provide the same answer as R but it's different from SPSS and I was wondering why? Given that the differences are quite substantial.

Thank you in advance for any advice.
Susanne

#In R
lm(formula = CPSST_8rank ~ sert_tri_bin, data = DataInc)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-69.622  -52.454    0.046   40.546   82.046  

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)    57.787     10.921   5.291 4.08e-07 ***
sert_tri_bin   17.167      8.359   2.054   0.0417 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for gaussian family taken to be 1975.892)

    Null deviance: 314598  on 156  degrees of freedom
Residual deviance: 306263  on 155  degrees of freedom
AIC: 1641

In JASP:

Same as R

In SPPS (sorry for the formating):

Model Summary                                   
Model   1 R (.288a) R Square (.083) Adjusted R Square (.077)    Std. Error of the Estimate   (35.40)    R Square Change (.083)  F Change (14.017) df1 (1)       df2 (155)       Sig. F Change (.000)

a Predictors: (Constant), sert_tri_bin                                  

ANOVAa                      
Model       Sum of Squares      df          Mean Square         F           Sig.
1   
Regression  17569.313           1           17569.313           14.017      .000b
Residual        194276.068          155         1253.394        
    Total   211845.381          156         
a Dependent Variable: CPSST_8rank                       
b Predictors: (Constant), sert_tri_bin                      

EJ

I am not sure what outputs to compare, exactly, but I googled this problem and it has been noted a few times before. From what I see, most of the time the issue is rounding (!). For instance see https://stats.stackexchange.com/questions/113314/spss-and-stata-output-different
It's great that you've also posted this issue on our GitHub page. We might take a while to get to this, but we will at some point.
E.J.

EJ

Susanne, on GitHub you said that you resolved the issue. What was the cause of the discrepancy?
Cheers,
E.J.