Actual StataMP numerical output. Log header and machine paths omitted. . regress score str, vce(robust) Linear regression Number of obs = 420 F(1, 418) = 19.26 Prob > F = 0.0000 R-squared = 0.0512 Root MSE = 18.581 ------------------------------------------------------------------------------ | Robust score | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- str | -2.279808 .5194892 -4.39 0.000 -3.300945 -1.258671 _cons | 698.933 10.36436 67.44 0.000 678.5602 719.3057 ------------------------------------------------------------------------------ . * END simple . scalar simple_b = _b[str] . scalar simple_se = _se[str] . scalar simple_a = _b[_cons] . * BEGIN contrast . lincom -2*str ( 1) - 2*str = 0 ------------------------------------------------------------------------------ score | Coefficient Std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- (1) | 4.559617 1.038978 4.39 0.000 2.517343 6.60189 ------------------------------------------------------------------------------ . * END contrast . * BEGIN adjusted . regress score str el, vce(robust) Linear regression Number of obs = 420 F(2, 417) = 223.82 Prob > F = 0.0000 R-squared = 0.4264 Root MSE = 14.464 ------------------------------------------------------------------------------ | Robust score | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- str | -1.101296 .4328472 -2.54 0.011 -1.95213 -.2504616 el | -.6497768 .0310318 -20.94 0.000 -.710775 -.5887786 _cons | 686.0322 8.728224 78.60 0.000 668.8754 703.189 ------------------------------------------------------------------------------ . * END adjusted . scalar adjusted_b = _b[str] . scalar adjusted_se = _se[str] . scalar adjusted_a = _b[_cons] . scalar el_b = _b[el] . * Same observations: the coefficient change is not a sample change. . assert e(N)==420 . * BEGIN adjusted_contrast . lincom -2*str ( 1) - 2*str = 0 ------------------------------------------------------------------------------ score | Coefficient Std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- (1) | 2.202592 .8656943 2.54 0.011 .5009232 3.90426 ------------------------------------------------------------------------------ . * END adjusted_contrast . * Independent numerical checks of the OLS normal equations. . predict double residual, residuals . quietly summarize residual . assert abs(r(mean)) < 1e-8 . generate double orth = residual*str . quietly summarize orth . assert abs(r(mean)) < 1e-6 . export delimited score str el using "output/schools.csv", replace file output/schools.csv saved . file open stats using "output/schools_stats.csv", write replace . file write stats "model,intercept,slope,se,el_slope,n" _n . file write stats "simple," (simple_a) "," (simple_b) "," (simple_se) ",0,420" _n . file write stats "adjusted," (adjusted_a) "," (adjusted_b) "," (adjusted_se) "," (el_b) ",420" _n . file close stats . display "ECO603_MEETING_01_COMPLETE" ECO603_MEETING_01_COMPLETE Actual StataMP numerical output. Log header and machine paths omitted. . * BEGIN short . regress score str, vce(robust) Linear regression Number of obs = 420 F(1, 418) = 19.26 Prob > F = 0.0000 R-squared = 0.0512 Root MSE = 18.581 ------------------------------------------------------------------------------ | Robust score | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- str | -2.279808 .5194892 -4.39 0.000 -3.300945 -1.258671 _cons | 698.933 10.36436 67.44 0.000 678.5602 719.3057 ------------------------------------------------------------------------------ . * END short . record short str . * BEGIN long . regress score str el, vce(robust) Linear regression Number of obs = 420 F(2, 417) = 223.82 Prob > F = 0.0000 R-squared = 0.4264 Root MSE = 14.464 ------------------------------------------------------------------------------ | Robust score | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- str | -1.101296 .4328472 -2.54 0.011 -1.95213 -.2504616 el | -.6497768 .0310318 -20.94 0.000 -.710775 -.5887786 _cons | 686.0322 8.728224 78.60 0.000 668.8754 703.189 ------------------------------------------------------------------------------ . * END long . record long str . record language el . * BEGIN auxiliary . regress el str Source | SS df MS Number of obs = 420 -------------+---------------------------------- F(1, 418) = 15.25 Model | 4932.98526 1 4932.98526 Prob > F = 0.0001 Residual | 135170.2 418 323.373684 R-squared = 0.0352 -------------+---------------------------------- Adj R-squared = 0.0329 Total | 140103.185 419 334.375143 Root MSE = 17.983 ------------------------------------------------------------------------------ el | Coefficient Std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- str | 1.813719 .4643735 3.91 0.000 .9009206 2.726517 _cons | -19.85405 9.162604 -2.17 0.031 -37.86458 -1.843531 ------------------------------------------------------------------------------ . * END auxiliary . record auxiliary str . * BEGIN income . regress score str el income, vce(robust) Linear regression Number of obs = 420 F(3, 416) = 299.03 Prob > F = 0.0000 R-squared = 0.7072 Root MSE = 10.347 ------------------------------------------------------------------------------ | Robust score | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- str | -.0687755 .2901597 -0.24 0.813 -.6391376 .5015865 el | -.4882667 .0281161 -17.37 0.000 -.543534 -.4329995 income | 1.494517 .09156 16.32 0.000 1.314539 1.674495 _cons | 640.3155 5.991918 106.86 0.000 628.5373 652.0937 ------------------------------------------------------------------------------ . * END income . record income str . export delimited score str el income using "output/meeting_02_data.csv", replace (file output/meeting_02_data.csv not found) file output/meeting_02_data.csv saved . . postclose results . use "output/meeting_02_estimates.dta", clear . export delimited using "output/meeting_02_estimates.csv", replace (file output/meeting_02_estimates.csv not found) file output/meeting_02_estimates.csv saved . display "ECO603_MEETING_02_COMPLETE" ECO603_MEETING_02_COMPLETE Actual StataMP numerical output. Log header and machine paths omitted. . * BEGIN full . regress score str el income, vce(robust) Linear regression Number of obs = 420 F(3, 416) = 299.03 Prob > F = 0.0000 R-squared = 0.7072 Root MSE = 10.347 ------------------------------------------------------------------------------ | Robust score | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- str | -.0687755 .2901597 -0.24 0.813 -.6391376 .5015865 el | -.4882667 .0281161 -17.37 0.000 -.543534 -.4329995 income | 1.494517 .09156 16.32 0.000 1.314539 1.674495 _cons | 640.3155 5.991918 106.86 0.000 628.5373 652.0937 ------------------------------------------------------------------------------ . * END full . record full str . scalar full_b=_b[str] . quietly regress score el income . predict double ry, residuals . quietly regress str el income . predict double rx, residuals . * BEGIN fwl . regress ry rx, noconstant Source | SS df MS Number of obs = 420 -------------+---------------------------------- F(1, 419) = 0.06 Model | 6.60482474 1 6.60482474 Prob > F = 0.8033 Residual | 44540.7318 419 106.302463 R-squared = 0.0001 -------------+---------------------------------- Adj R-squared = -0.0022 Total | 44547.3367 420 106.065087 Root MSE = 10.31 ------------------------------------------------------------------------------ ry | Coefficient Std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- rx | -.0687755 .2759147 -0.25 0.803 -.6111251 .473574 ------------------------------------------------------------------------------ . * END fwl . record partial rx . assert abs(_b[rx]-full_b)<1e-8 . * BEGIN vif . quietly regress score str el income . estat vif Variable | VIF 1/VIF -------------+---------------------- income | 1.14 0.873929 el | 1.12 0.891206 str | 1.07 0.931159 -------------+---------------------- Mean VIF | 1.11 . * END vif . export delimited score str el income rx ry using "output/meeting_03_data.csv", replace (file output/meeting_03_data.csv not found) file output/meeting_03_data.csv saved . . postclose results . use "output/meeting_03_estimates.dta", clear . export delimited using "output/meeting_03_estimates.csv", replace (file output/meeting_03_estimates.csv not found) file output/meeting_03_estimates.csv saved . display "ECO603_MEETING_03_COMPLETE" ECO603_MEETING_03_COMPLETE Actual StataMP coefficient-only results. Log header omitted. . import delimited "output/meeting_02_data.csv", clear varnames(1) asdouble (encoding automatically selected: ISO-8859-1) (4 vars, 420 obs) . * BEGIN simple . quietly regress score str . matrix list e(b), format(%10.6f) e(b)[1,2] str _cons y1 -2.279808 698.932953 . * END simple . * BEGIN contrast . display %10.6f -2*_b[str] 4.559617 . * END contrast . * BEGIN adjusted . quietly regress score str el . matrix list e(b), format(%10.6f) e(b)[1,3] str el _cons y1 -1.101296 -0.649777 686.032250 . * END adjusted . * BEGIN adjusted_contrast . display %10.6f -2*_b[str] 2.202592 . * END adjusted_contrast . * BEGIN auxiliary . quietly regress el str . matrix list e(b), format(%10.6f) e(b)[1,2] str _cons y1 1.813719 -19.854055 . * END auxiliary . * BEGIN income . quietly regress score str el income . matrix list e(b), format(%10.6f) e(b)[1,4] str el income _cons y1 -0.068776 -0.488267 1.494517 640.315497 . * END income . quietly regress score el income . predict double ry, residuals . quietly regress str el income . predict double rx, residuals . * BEGIN partial . quietly regress ry rx, noconstant . matrix list e(b), format(%10.6f) symmetric e(b)[1,1] rx y1 -0.068776 . * END partial . display "ECO603_COEFFICIENT_WORKSHOP_COMPLETE" ECO603_COEFFICIENT_WORKSHOP_COMPLETE