How missing values are covered by PLP

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When taking a look at results of PLP, we have found an interesting thing:
for some of our covariates based on measurement values CovariateCountWithOutcome ( as well as CovariateCountWithNoOutcome) are much less then expected.
For example, body mass index (BMI) values are around 13, while direct look at data shows values ~ 21.

As far as I understand the problem is that not all subjects included into the study do have this measurement results.So for the rest of subjects covariate values are considered as 0
Can anyone confirm if this is an actual behavior of the package?
@Rijnbeek, @jreps, any thoughts will be appreciated.

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Hi, I’m youjin.
Recently, I’m trying to develop a PLP model using measurement values too.
you can see what happens if there were missing measurement values in the Book of OHDSI chapter 13,

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The book said PLP package inserts them as 0.

So, I used to (1) use the measurement values without missing and (2) exclude the measurement concepts with many missing. And sometimes, I (3) excluded the patients with missing when I use measurement value as covariates.

I think talking about data missing when we use measurement values in PLP is a good topic.

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