DEEPCAUSAL Procedure

Functional Summary

The statements and options available in the DEEPCAUSAL procedure are summarized in Table 1. The sections after the table provide a description of each statement in alphabetical order, following the PROC DEEPCAUSAL statement.

Table 1: Functional Summary

Description Statement Option
Input Data Table Option
Specifies the input data table PROC DEEPCAUSAL DATA=
Specifies the input data table for alpha left-parenthesis dot right-parenthesis estimation information SCORE INA=
Specifies the input data table for beta left-parenthesis dot right-parenthesis estimation information SCORE INB=
Specifies the input data table for outcome model information SCORE INO=
Specifies the input data table for propensity score model information SCORE INPS=
Output Data Table Options
Writes the estimation of the parameters of interest, policy evaluation, and policy comparison to an output data set INFER OUTEST=
Writes the details of the estimation, including alpha left-parenthesis dot right-parenthesis, beta left-parenthesis dot right-parenthesis, p left-parenthesis dot right-parenthesis, the residual, and influence functions for each unit, to an output data set INFER OUTDETAILS=
Writes the alpha left-parenthesis dot right-parenthesis estimation information to the specified output data set SCORE OUTA=
Writes the beta left-parenthesis dot right-parenthesis estimation information to the specified output data set SCORE OUTB=
Writes the outcome model information to the specified output data set SCORE OUTO=
Writes the propensity score model information to the specified output data set SCORE OUTPS=
ID Variable
Specifies the identifying variable ID
Deep Neural Network (DNN) Options
Specifies the parameters of the DNN for the propensity score model PSMODEL DNN=
Specifies the parameters of the DNN for the outcome model MODEL DNN=
Specifies the number of nodes for all hidden layers of the DNN for the propensity score model and outcome model DNN NODES=
Specifies the training options of the DNN for the propensity score model and outcome model DNN TRAIN=
Outcome Model Variables
Specifies the outcome variable MODEL outcome-variable
Specifies the covariates for the outcome model MODEL covariates
Propensity Score Model Variables
Specifies the treatment variable PSMODEL treatment-variable
Specifies the covariates for the propensity score model PSMODEL covariates
Inference Options
Specifies the list of policy variables to be evaluated INFER POLICY=
Specifies the parameters for policy comparison INFER POLICYCOMPARISON=


Last updated: November 24, 2025