At this moment, I am busy running a Generalized Estimating Equations model in SPSS. Unfortunately, I cannot use an ordinary logistic regression as the conditions are repeated measures.
I asked people to indicate whether they should click on a search engine result. These results were manipulated by position (low = 0, high = 1), description (short = 0, long = 1) and type of result (non-sponsored = 0, sponsored = 1). Click intention is measured by either clicking (1) or not clicking (0) on the result. These were added to the model, including two interactions terms (PositionType and DescriptionType).
Underneath the parameter estimates of the GEE.
I know it's important to look at the interaction terms first: position*type seems to be significant. However, I would like to make a chart where I point out the differences in position and description by type. Unfortunately, I do not have a clue where to start and how to interpret these numbers.