u/Walkill996

Hi all. I am using a zero-inflated negative binomial model to evaluate the change in the number of prescriptions for drug A following a treatment. The treatment is modeled as a time-varying covariate and patients initiate treatment at different times during follow-up. All patients have received this treatment so each patient contributes both unexposed and exposed person-time.

My main confusion is about the zero-inflation component of the model. I understand that the count component should include the exposure and confounders of interest. I couldn't find accurate literature about variable selection for the zero-inflation part.

My model is like:

fit <- zeroinfl(n_prescriptions ~ treatment + age + sex + poverty+ education+ offset(log(follow_up_time)) | treatment + age + sex + poverty+ education, data = df, dist = "negbin")

Is there any general principle for selecting variables for the zero-inflation component? Should it contain the same covariates as the count component, or only exposure variables? Thank you.

在一个音乐节上我吃了一点happy caps，是一种混合了lsa，咖啡因，cbd的胶囊，每样成分都只有一点，吃起来类似microdosing的感觉，在音乐节上一切感觉都好。但是回程途中因为是散场，所以和一群人挤公交，车里非常闷热，周围每个人又在大声说话，还有人放起了节奏很快的音乐。突然我感觉到自己有些不舒服，像要进入一个漩涡，越陷越深，要喘不过气的感觉，我马上就意识到是不是焦虑被触发了，整个感觉持续了可能有一分钟，这时候公交停了，我立马下车，在路边坐了一会吹了一会风才感觉好多了。
本来我以为这个东西效果这么轻，应该没什么事，看来还是不能忽视可能的副作用。