Hi all,
I have a question with regards to principal component analysis. On the basis of pca, I created several indices which will serve as the outcome variables in my PSM algorithm. However, I am struggling to understand the meaning of the outcomes below. I used the following code:
If I understand correctly, all my outcome are significant (based df=298). So, it can be said that the intervention had a positive effect on e.g. pcamaterial1, However, I have the following questions:
1. Looking at pcamaterial1, how to understand the ATT of 2.57
2. The t-stats of both the unmatched and ATT are similar, does that have to do something with the covariates and/or the algorithm that I implemented?
Would be great if someone can help me with this!
I have a question with regards to principal component analysis. On the basis of pca, I created several indices which will serve as the outcome variables in my PSM algorithm. However, I am struggling to understand the meaning of the outcomes below. I used the following code:
Code:
psmatch2 round age_1 i.schoolatt howmanyHHM_1 i.partner i.childmortality schoolagedchildren_1 , out (pcamaterial1 pcamaterial2 pcaenvir > onmental1 pcapersonal1 pcapersonal2 pcapersonal3 pcapersonal4) kernel kerneltype(epan) bwidth(.05)
If I understand correctly, all my outcome are significant (based df=298). So, it can be said that the intervention had a positive effect on e.g. pcamaterial1, However, I have the following questions:
1. Looking at pcamaterial1, how to understand the ATT of 2.57
2. The t-stats of both the unmatched and ATT are similar, does that have to do something with the covariates and/or the algorithm that I implemented?
Would be great if someone can help me with this!
