I am working with a binary logistic regression in SPSS and my current issue is that my baseline model is not significant (0.440) (Block 0 "Variables in the Equation), my Omnibus-test however is and the Chi-squared value is pretty high (171.162 for 15 df). When I include my independent variables I get some pretty good results that are significant and have interesting odds-ratios for my analysis (Block 1).

Does the non-significant value of my baseline model mean that I can't make any significant implications for the analysis, or can I disregard the insignificance in the baseline model? Is there any way to make it significant?

It's a social science research project with 988 respondents.


1 Answer 1


No, it doesn't mean that. The model with the intercept is usually uninteresting and whether the intercept is significant isn't important. I don't think there's a sensible way of making the intercept significant, but there's no reason to do so.

So, you can add independent variables.


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