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Hello everyone! This week I want to show you a little trick that will make your life easier in case you have missing covariate values in your data. Just as a recall, as we show in the FoW 89, if some values are missing in your data for a categorical covariate for just some individuals, you can have a dot in the data for these individuals and the dataset is accepted. Monolix creates an additional category NA and you can decide in the statistical model tab how to group this category with the others. For continuous covariates, such as AGE, it is not possible to just have a dot for missing values. You can for example decide here to assign a typical value which would be the median of AGE for all other individuals which is in this case around 31. But you could also assign the mean AGE which is around 41. Will this imputed value influence my covariate effects? You dont want to modify the data each time you test a hypothesis. The trick here is to instead give a value that is out of range for