txt"Import data"
	import delimited "/Users/matthewnudelman/Desktop/Storage/School/UCSF/2019 8. Spring/EPI265/HW/HW9/Book1.csv", encoding(ISO-8859-1) clear

txt"Treatment = Alendronate"
txt"Mediator = Bone Mineral Density"
txt"Outcome = Vertebral fractures"	
	
txt"Create treatment (Alendronate)"	
	gen newtx = 0 if tx =="Placebo"
		replace newtx = 1 if tx =="Alendronate"
		drop tx
		rename newtx tx

txt"Create outcome (spinal fracture)"		
	gen new_vfx2 = 0 if new_vfx =="no"
		replace new_vfx2 = 1 if new_vfx =="yes"
		drop new_vfx
		rename new_vfx2 new_vfx	
	
txt"Create mediator (Bone mineral density BMD)"	
	gen bmd_ch = fwp_bmd - bl_bmd

txt"Select 10,000 sample size"
sample 10000, count

txt"Baron and Kenny approach" 
		txt"First I'll calculate the DIRECT effect"
			logistic new_vfx i.tx bmd_ch
				matrix define ebd = e(b)
				scalar direct=ebd[1,2] 
				di exp(direct)
		txt"Next, I'll calculate the TOTAL effect "
			logistic new_vfx i.tx
				matrix define ebt = e(b)
				scalar total=ebt[1,2] 
				di exp(total)
		txt"Last, I'll calculate the % mediated with confounder using logit coefficients"
			di (total-direct)/total
			
txt"Calculating Controlled Direct Effect (CDE) "
	txt"I'll do this by fitting two models about how the treatment effects 1) the mediator and 2) the outcome"  
		qui regress bmd_ch i.tx 
		qui logistic new_vfx i.tx 
	txt"Create interaction term between mediator and treatment"
		 gen tx_bmd_ch = tx*bmd_ch
	txt"Using the Medeff command"
		 medeff ///
			(regress bmd_ch tx)  ///
			(logit new_vfx tx bmd_ch tx_bmd_ch), ///
			mediate(bmd_ch) treat(tx) interact(tx_bmd_ch)