# Non-monotone missing data, and inverse probability weighting

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