I am trying to conduct a logistic regression after propensity score matching. I tried both gmatch psmatch2 and am wondering if I should expect similar result from both? For example :
webuse cattaneo2, clear
rename order orderb
* Using GMATCH
logistic mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby
predict ps
gmatch mbsmoke ps, maxc(1) set(set1) diff(diff1)
logistic deadkids i.mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby if set1 < .
**
* uisng PAMATCH2
psmatch2 mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby, outcome(deadkids) neighbor(1)
logistic deadkids i.mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby [fweight=_weight]
Should I expect similar result for the logistic regression after running the above commands?
Actually in this case the results were close.
************************************************** ************************************************** ************************************************** *****
However, I am doing a similar analysis using another dataset. I run the commands as below:
use mydata, clear
USING GMATCH
logistic disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n
predict ps
gmatch disability_child ps, maxc(1) set(set1) diff(diff1)
logistic k6cat2v2 i.disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n if set1 < .
**
USING PSMATCH2
psmatch2 disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n, outcome(k6cat2v2) neighbor(1)
logistic k6cat2v2 i.disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n [fweight=_weight]
However, the results are far from similar. Some values are above or below 0, just the opposite. Why is that so?
I want to use psmatch2. Also, I want to produce descriptive table of the matched cases and control after psmatch2. How can I do so?
webuse cattaneo2, clear
rename order orderb
* Using GMATCH
logistic mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby
predict ps
gmatch mbsmoke ps, maxc(1) set(set1) diff(diff1)
logistic deadkids i.mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby if set1 < .
**
* uisng PAMATCH2
psmatch2 mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby, outcome(deadkids) neighbor(1)
logistic deadkids i.mbsmoke i.mrace i.foreign mage medu fage fedu prenatal orderb i.frace i.mmarried i.fbaby [fweight=_weight]
Should I expect similar result for the logistic regression after running the above commands?
Actually in this case the results were close.
************************************************** ************************************************** ************************************************** *****
However, I am doing a similar analysis using another dataset. I run the commands as below:
use mydata, clear
USING GMATCH
logistic disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n
predict ps
gmatch disability_child ps, maxc(1) set(set1) diff(diff1)
logistic k6cat2v2 i.disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n if set1 < .
**
USING PSMATCH2
psmatch2 disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n, outcome(k6cat2v2) neighbor(1)
logistic k6cat2v2 i.disability_child i.healthCond_cat2 i.affectLife i.symptom i.ageCat3 i.workingHourPerWeek_cat4 i.singleFather_n [fweight=_weight]
However, the results are far from similar. Some values are above or below 0, just the opposite. Why is that so?
I want to use psmatch2. Also, I want to produce descriptive table of the matched cases and control after psmatch2. How can I do so?
