I am trying to use SAS to fit an instrumental variable analysis on a binary outcome. From what I could find online, this can be done using the 2SLS estimator in proc syslin?
The data are as follows: death (outcome, yes/no), gene (exposure, class variable), which regulates "normalized" (mediator, continuous variable). The value of "normalized" is also affected by cohort, female, trg_i, and crp_log. What I want to know is:
1. If "normalized" (as an instrumental variable) is a causal risk factor for death.
2. If there is evidence for bias when using "normalized" as an observational variable vs. as an instrumental variable (using the Durbin-Wu-Hausman test) on risk of death.
Here is my code:
proc syslin data=causalmed 2sls; endogenous normalized; instruments gene cohort female trg_i crp_log; model normalized = gene cohort female trg_i crp_log; model death = normalized cohort female trg_i crp_log; run;
proc model data=causalmed; endogenous normalized; instruments gene; death = pnormalized*normalized + interc; fit death / ols 2sls hausman; quit;
Is my code correct? Any help would be much appreciated. Thanks!
Registration is open! SAS is returning to Vegas for an AI and analytics experience like no other! Whether you're an executive, manager, end user or SAS partner, SAS Innovate is designed for everyone on your team. Register for just $495 by 12/31/2023.
If you are interested in speaking, there is still time to submit a session idea. More details are posted on the website.