I have an experimental condition
(dummy-coded) as an categorical predictor, and one continuous predictor variable (treatment frequency).
The dependent variable (Y) is consumer satisfaction
This is an SPSS output,
My Q: is how to interpret the coefficients and Exp(B) of the categorical Variable and continuous predictor.
For Categorical variable: Is it correct to say " Condition 0 is .34 more effective than Condition 1 in enhancing consumer satisfaction. Or, can I say if the treatment frequency is fixed, Condition 0 compared to Condition 1 will increase the odds of satisfaction by 0.40." ?
For continuous predictor: Is it correct to say " When 1 unit increases in frequency, the satisfaction increase by .15 when the condition is 1. Or, if the condition is fixed to 1, treatment frequency will increase the odds of satisfaction by 0.17." ?
My last question is how to interpret the significant interaction term. Could you help me interpret the interaction term using the coefficient and also Exp(B)?
If you can recommend an published article that describe results from generalized linear model using interaction term, that'd be appreciated. Thank you.