I'm having difficulty identifying whether or not my missing data pattern is 'monotone'.
I have two variables with missing data, and the missing data patterns in each variable do not completely overlap. I.e., all the below combinations are possible:
A B 1 0 0 1 1 1 0 0 0 NA NA 0 NA 1 1 NA NA NA
Does this technically make my missing data pattern 'non-monotone'? Note that this is not repeated measures data - the two variables in question are independent of each other.
The reason I'm concerned about this is because I want to adjust for missingness using inverse probability weighting, and apparently it is debated whether or not this strategy can be used with non-monotone missing data.
Many thanks, Alice