Hi All,
I am running the DID regression model to estimate the treatment effect.
Prior to this, I have created the dataset using propensity score matching. So, I have matched pairs (each treated subject is matched to two nearest neighbours control subject).
I am using below code. However, this code does not account for the matched data.
Indeed, the matched pair should be the unit of analysis and I need to modify the below code to accout for the matched pairs
To make it clear, the below code considers all treated subjects versus all control subjects while I am looking for the differences between treated and control subject in each matched pair.
Thanks in advanced
/*Repeated measure linear regression*/
PROC MIXED DATA = Long; /* long format*/
CLASS A B;
MODEL Y=A|B covariatesX1 X2..Xn / SOLUTION;
LSMEANS A|B / DIFF;
ESTIMATE 'D-I-D' A*B 1 -1 -1 1;
RANDOM Int/SUBJECT= TYPE=UN ;
RUN;
Hi All,
I am running the DID regression model to estimate the treatment effect.
Prior to this, I have created the dataset using propensity score matching. So, I have matched pairs (each treated subject is matched to two nearest neighbors control subject).
I am using below code. However, this code does not account for the matched data.
Indeed, the matched pair should be the unit of analysis and I need to modify the below code to account for the matched pairs
To make it clear, the below code considers all treated subjects versus all control subjects while I am looking for the differences between treated and control subject in each matched pair.
Thanks in advanced
/*Repeated measure linear regression*/
PROC MIXED DATA = Long; /* long format*/
CLASS A B;
MODEL Y=A|B covariatesX1 X2..Xn / SOLUTION;
LSMEANS A|B / DIFF;
ESTIMATE 'D-I-D' A*B 1 -1 -1 1;
RANDOM Int/SUBJECT= TYPE=UN ;
RUN;
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