Excellent excellent excellent! Truly phenomenal discussion of the more advanced elements of PSM. I sincerely appreciated your precision in use of terms and concepts! Really helps those of us who are just starting out!
Do i use all possible baseline charateristics in this model, or do i only include variables that is not normally distrubuted before calculating propensityscores and afterwards using them for inverse probability weighting? So if i have 10 covariates and 6 is normally distrubuted between two groups, do i then only include the last 4 in this model?
very good explanation sir, u can also explain a little about logistic regression, machine learning in simple terms like orange and apples. Nice work sir
Excellent excellent excellent! Truly phenomenal discussion of the more advanced elements of PSM. I sincerely appreciated your precision in use of terms and concepts! Really helps those of us who are just starting out!
You did what many classes can't do!
love your work, keep it going king
Do i use all possible baseline charateristics in this model, or do i only include variables that is not normally distrubuted before calculating propensityscores and afterwards using them for inverse probability weighting? So if i have 10 covariates and 6 is normally distrubuted between two groups, do i then only include the last 4 in this model?
Thanks alot. your effort are excellent
Thanks very much sir
very good explanation sir, u can also explain a little about logistic regression, machine learning in simple terms like orange and apples. Nice work sir
😍
thank you very much. sir could you please share some state Do file please