ieddtable : first outline of command

Show how we want to first store all stats in a result matrix, and then pass that matrix to commands that create outputt according to the options used by user

src/ado_files/ieddtable.ado

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+
+	/* Create some dummy datat */
+
+	clear 
+
+	*set seed 12345
+	set obs 10000
+
+	gen tmt = (runiform()<.5)
+	gen t	= (runiform()<.5)
+
+	gen var_a = runiform()
+	gen var_b = runiform()
+	gen var_c = runiform()
+	gen var_d = runiform()
+
+
+	local varlist var_a var_b var_c var_d
+
+
+	/* the rest will be inside the command */
+
+	local colnames BC_Mean BC_err BT_Mean BT_err EC_Mean EC_err ET_Mean ET_err B1stDiff B1stDiff_err E1stDiff E1stDiff_err 2ndDiff 2ndDiff_err
+
+	*Define default row here. The results for each var will be one row that starts with all missing vlaues
+	mat startRow = (.,.,.,.,.,.,.,.,.,.,.,.,.,.)
+	mat colnames startRow = `colnames'
+
+	matlist startRow // See the default row with its column names
+
+	*Initiate the result matrix with a place holder row that will not be used for anything. Matrices cannot be initiated empty
+	mat resultMat = startRow
+	mat rownames resultMat = placeholder
+
+	*Loop over all varlist
+	foreach var of local varlist {
+
+		*Each variable is a row in the result matrix
+		mat `var' = startRow
+		mat rownames `var' = `var'
+		mat colnames `var' = `colnames'
+
+		*Local that keeps track of which column to fill
+		local colindex 0
+
+		*Get the means in each group
+		forvalues t01 = 0/1 {
+			forvalues tmt01 = 0/1 {
+
+				*Summary stats on this group
+				qui sum `var' if tmt == `t01' & t == `tmt01'
+
+				*Store the mean. Stored for all groups regardless if means or first differences will be displayed. Output sub-commands will select which one to use according to options used by user
+				local ++colindex
+				mat `var'[1,`colindex'] = `r(mean)'
+
+				*Store the standard deviation (allow the option for different variance here)
+				local ++colindex
+				mat `var'[1,`colindex'] = `r(sd)'				
+			}
+		}
+
+		*Run the regression to get the double difference
+		reg `var' tmt#t
+		mat resTable = r(table)
+		matlist resTable
+
+		*Loop over the two first difference coefficients and then over the second difference
+		forvalues coeffcolumn = 2/4 {
+
+			//Get the second differnce
+			local ++colindex
+			mat `var'[1,`colindex'] =  el(resTable,1,`coeffcolumn') 
+
+			*Get the standard error fo
+			local ++colindex
+			mat `var'[1,`colindex'] =  el(resTable,2,`coeffcolumn') 
+
+		}
+
+		*Append this row to the result table
+		mat 	resultMat = (resultMat \ `var')
+
+	}
+
+	*Show the final matrix will all data needed to start building the output
+	matlist resultMat
+
+	******
+	*Then the result matrix can be passed into subcommands that output in either Excel, LaTeX or in the main window.
+
+	*The results can be accessed like this, which makes the sub-commands less sensitive to changing column order in the section above.
+	mat A = resultMat[3, "BC_Mean"] // returns a 1x1 matrix
+	local a = el(A,1,1)				// returns the value
+
+	matlist A
+	di `a'
+