How to address missing value error in mgcv

When I try to run a model in mgcv I get the following error:

Error in while (mean(ldxx/(ldxx + ldss)) > 0.4) { : 
  missing value where TRUE/FALSE needed

My syntax is based on the 2019 paper 'Analyzing the Time Course of Pupillometric Data' by van Rij et al. This is the syntax I used:

m2.flanker <- bam(pupil_normed ~ condition 
                   + s(time, by=condition, k=20)
                   + s(x_coord, y_coord)
                   + s(time, id, bs='fs', m=1)
                   + s(time, TRIAL_INDEX, bs='fs', m=1)
                   + s(EVENT, bs='re') 
                   + s(time, EVENT, bs='re')
                   , data=dat.flank1, discrete=T)

I then run into the error posted above. I looked at the supplementary materials from the paper, and looked at the missigness/data structure and found it to be similar to mine (some missing data, but in the same places I had missing data). I tried to run the syntax provided with their data:

m5 <- bam(Pupil ~ Condition + s(Time, by=Condition, k=20) 
           + s(Xgaze, Ygaze)
           + s(Time, Subject, bs='fs', m=1) + s(Time, Item, bs='fs', m=1)
           + s(Event, bs='re') + s(Time, Event, bs='re')
           , data=dat0, discrete=TRUE)

I did not get any error. I'm unclear why I get the error when I run the model with my data, but not with the data the authors use. Also, the error is pretty clearly related to the EVENT factor in my data, if I remove it I don't get an error.