# Thread: SPSS..model 1 or 2?

1. ## SPSS..model 1 or 2?

I`m doing multiple regression in SPSS with Enter-method. The output i use is Model summary, ANOVA, and Coefficients.

I`ve put in some control variables/covariates , and SPSS shows this as model 1 and model 2 with and without the control variables.

But which of these models should i choose to report?
Is it model 1, where model 2 is just to show how the control variables effect the independent variable(s)?
That is at least what i`ve done for now. But i`m pondering if i should choose model 2 if the R-square of the model is higher than model 1? Or if the control variable is significant?

I haven`t found anything on google or guides to point me in any direction regarding this...

2. Choose the model whose R-Square is higher.

3. Originally Posted by Dr.Appalayya
Choose the model whose R-Square is higher.
Thank you very much. I suspected it, though it was either the Beta-coefficients or the R-square i thought about as decisive..and if the control variables were significant thay might have to be taken into account. But i`ll go with the easy and sensible "R-square" alternative. ;-)

4. Originally Posted by Dr.Appalayya
Choose the model whose R-Square is higher.
Be careful when doing that. The model with more parameters will always have a higher R-square value. Does SPSS have an "adjusted" R-square value? Some statistical software will calculate that to try and account for the number of parameters in the model.

Be careful when doing that. The model with more parameters will always have a higher R-square value. Does SPSS have an "adjusted" R-square value? Some statistical software will calculate that to try and account for the number of parameters in the model.

Yes, SPSS have the adjusted R-square for the model.
Example (Roughly edited from SPSS table... Model 2 consists of independent/dependent and control variables):

Model Summary(c)
Model R R Square Adjusted R Square Std. Error of the Estimate
1 R =,481(a) R-Square= ,232 Adjusted R Square= ,225 Std.error of the estimate= ,99145

2 R= ,487(b) R Square= ,237 Adjusted R Square= ,215 Std. error of the estmate= ,99740

a Predictors: (Constant), Market orientation
b Predictors: (Constant), Market orientation, Belongs to a hotel chain, Number of employees in the hotel
c Dependent Variable: Information Quality

or....

Model Summary(c)
Model R R Square Adjusted R Square Std. Error of the Estimate
1 Model R,569(a) R Square= ,323 Adjusted R Square= ,310 Std. Error of the estimate= ,89136
2 Model R,582(b) R Square= ,339 Adjusted R Square= ,320 Std. Error of the estimate= ,88512

a Predictors: (Constant), AnalyticalCRM, Information Quality
b Predictors: (Constant), AnalyticalCRM, Information Quality, Number of employees in the hotel
c Dependent Variable: Marketing Innovation

I`ve seen my peers using R Square..not Adjusted R Square. But i`ve also seen Adjusted R Square being used in some tutorial (not related to my studies). I do not use a lot of variables in the model(s). SPSS can only run one dependent variable at the time, and i have two control variables (at most) along with max two other independent variables.

6. I'm not sure what you're trying to do between the top two and the bottom two models. However, looking at the top two models, it looks like model 2 is a better fit.

I'm not surprised that a lot of your peers use r-square. Its very straight forward and easy to understand. However, there still should be caution when using it.

You should take a step back though and think about what it is that you're really trying to answer. What is your question? My co-worker/mentor always tells me that I should have that in the front of my mind, and that the question should then guide how I set up my models. Any fool can throw in variables and get results. Good models require lots of thought though.

HTH

7. I would try running this model via the generalized linear model (SPSS got it), and then you can compare the models using AIC and BIC

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