Hi all,
I am trying to figure out how to handle missing observations for the non-affected firms in an interaction using logistic regression. I have two outcomes for my dependent variable: companies that get targeted by a journalist (1) and companies that do not get targeted by a journalist (0). I can run a main effect, where I look at the effect of CEO gender on activism. Straightforward.
Now I want to test an interaction whether I interact CEO gender X journalist experience to see whether journalists' experience moderates the relationship between CEO gender and probability of targeting by a journalist. However, the issue I am facing is that I only have journalist experience data for companies that were actually targeted by a journalist (1), and nothing for companies that do not get targeted (0).
I see two ways to handle this:
1. I code journalist experience as 0 for all companies that do not get targeted (0)
2. I only analyze the the subsample of companies that get targeted by a journalist (1) and look at the moderating effects of journalist experience within that group. However, I do not see how I can do this since the outcome (targeted) never varies (i.e., it is always 1).
Any advice on how to handle this dilemma would be appreciated.
Roger
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