Q Is there anything wrong with adding number of trials per par | Data Scientology

Q Is there anything wrong with adding number of trials per participant as a predictor in a mixed effects model?

I have data from a remember/know task. In this task participants learn words, then are tested on the previously seen words plus new lures. They have three options for each word: I remember seeing this word, I know I saw this word, I did not see this word. (I won't get into the theory on why these are different responses, but can add references if anyone is interested.)

Anyway, I am running a mixed effects model only on words that they respond to with "remember" or "know". The DV is whether they said remember or know, and I have various lexical properties as predictors.

This means that there will be a different number of observations per participant (as the number of "new" responses will differ). I would like to account for this. Is there any downside to including the number of trials per participant as a predictor?

(BTW I don't think a multinomial model with three response options and all trials included is what I want. I am only interested in remember vs know.)

/r/statistics
https://redd.it/v1y480