What kind of datasets are accepted by Causal-MGM?

[gl97at]

Hi there,

I have a mixed dataset that consists of numerical (continuous and discrete values) variables and categorical variables (with max 3 different categories per variable). Some values, in both types of variables, are missing. Thus, they are represented by an *. According to the User Guide, missing values are not accepted, but it does not make sense to replace my missing values with any other value. As a result, missing values have to be retained. In that case, is Causal-MGM an appropriate tool? What should I do?

I have another dataset that consists of only numerical (continuous values) variables. According to the User Guide, Causal-MGM needs a mixed dataset (numerical and categorical variables). In that case, is Causal-MGM an appropriate tool? What should I do, in order to use the tool?

Thank you in advance!