![]() Linear regression, absorbing indicators Number of obs = 6209ĭocvis | Coef. The standard weights are 1 for all persons. PWEIGHT allows for differential weighting of persons. Note: female omitted because of collinearity In the analysis I reweight using reg y x pwipw I found the following description of pweighting online: PWEIGHT person (case) weighting. ![]() Why is that? areg docvis hhkids age agesq married working linc addon female fekid, absorb(id) Why is this? Why is female omitted? I assume that this is due to the multicollinearity between female and fekids, however when I do an OLS regression this does not happen. 04)) is significant and negatively associated with the Dependent variable(DV) in the regression at the 1 level. I was told by someone that I do not need to include female. I have included the variable female in my regression. My chatgpt command uses a combination of Stata and Python code. That women with children are 15.77% less likely to visit the hospital than men with children are. ![]() I have interpreted from the coefficient on fekids that women's hospital visits ARE more affected than men's. I wanted to see whether women's hospital visits are more affected by having children than men's. hhkids refers to whether or not a person has kids. I created an interaction term between hhkids and female called fekids. Last season, Jacksonville finished as one of the best offenses in the league, ranking 10th in total offense in 2022 with 357.4 yards per game. The dependent variable docvis refers to hospital visits. I am carrying out a fixed effect regression.
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