Hi community I'm currently working on research in self-harming behaviour. I have a large longitudinal dataset, and I am investigating the effect of hyperactivity difficulties in the early childhood on the risk of developing self-harming behavior as adolescent. I now want to investigate which possible mediating effects there might be between the two. So I have the following model: Y = selfharm (binary) treatment=hyperactivity in early childhood (scale on 0-20) covariates: female (binary), divorced(binary), smoking(binary), peer_dif (scale on 0-10) and mater_menta (continous) I then have several mediators such as psychiatric disorders, SDQ measures, addiction etc. which I want to test at the same time. But 'proc causalmed' can only handle one mediator. I then looked at 'Example 2' in this link: https://support.sas.com/kb/59/081.html but as far as I can see, this example is without covariates. So my question is, if there is a way I can do a mediation analysis with multiple mediators and covariates? I'm using SAS Studio.. I have thought of first running a logistic regression, controlling self-harm for the covariates, but not hyperactivity, and then save the residual and use the residuals as my Y. But I'm not sure if that would make any sense. Thank you for your time,
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