I'm new to logistic regression and the project I'm working on requires a model that involves two predictors:

So, one categorical predictor and one continuous predictor. But, these two things should interact! So, we get:

I have one dependent variable that is binary.

When I run my analysis in SPSS I get a

In other words, I'm not sure what B-values to report when I write up my results.

I was using Andy Field's book

Sorry if my question seems silly, I am new to this procedure and was not formally educated on how to use it!

Any help would be appreciated!

- Experimental condition (categorical variable with 8 categories)
- Score on a measure (continuous variable)

So, one categorical predictor and one continuous predictor. But, these two things should interact! So, we get:

- Experimental condition
- Score
- Experimental condition * score

I have one dependent variable that is binary.

When I run my analysis in SPSS I get a

**Variables in the Equation**table that has a*lot*of information and I'm not sure which information is important. I seem to be getting a B-value for every experimental condition, but no B-value for experimental conditions overall. I'm also getting a B-value for every interaction between the scores and the experimental conditions, but no overall B-value for that interaction.In other words, I'm not sure what B-values to report when I write up my results.

I was using Andy Field's book

*Discovering Statistics using SPSS for Windows*to walk through logistic regression, but he doesn't explain how to interpret a situation like this.Sorry if my question seems silly, I am new to this procedure and was not formally educated on how to use it!

Any help would be appreciated!

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