-------------------------------------------------------------------------------------------------------------------------------------------------- log: G:\Yu\research\Health Economics\2010\table6.log log type: text opened on: 16 Jun 2010, 00:06:41 . sort with_p; . tabstat bmi withkid uninsured smoke educ age employed black hispanic othrace married if !male, by(with_p) > stat(mean, sd) col(stat) longstub nototal; with_p variable | mean sd ----------------------+-------------------- 0 bmi | 25.62744 5.502517 withkid | .5338346 .4989879 uninsured | .2094522 .407027 smoke | .2561762 .4366375 educ | 13.41783 2.379264 age | 25.70838 3.260551 employed | .622986 .4847686 black | .1573577 .3642355 hispanic | .1568206 .3637292 othrace | .0741139 .2620265 married | .5343716 .4989512 ----------------------+-------------------- 1 bmi | 23.84183 5.106826 withkid | .4032445 .4908335 uninsured | .1216686 .3270922 smoke | .1807648 .3850463 educ | 13.26767 1.735118 age | 21.06141 2.926744 employed | .6199305 .4856851 black | .0764774 .2659145 hispanic | .0880649 .2835536 othrace | .032445 .1772814 married | .5979143 .4906034 ------------------------------------------- . tabstat bmi withkid uninsured smoke educ age employed black hispanic othrace married if male, by(with_p) > stat(mean, sd) col(stat) longstub nototal; with_p variable | mean sd ----------------------+-------------------- 0 bmi | 26.55467 4.61291 withkid | .3532487 .4781577 uninsured | .3024645 .4594969 smoke | .3188947 .4662223 educ | 13.15907 2.541011 age | 25.57655 3.32168 employed | .8140403 .3892195 black | .1344287 .3412398 hispanic | .1926811 .3945521 othrace | .068708 .2530514 married | .4794623 .4997647 ----------------------+-------------------- 1 bmi | 25.01645 4.624936 withkid | .2709677 .4446986 uninsured | .1870968 .390199 smoke | .2731183 .4458008 educ | 12.82581 1.706626 age | 21.02043 2.855435 employed | .6354839 .4815532 black | .0580645 .2339912 hispanic | .0612903 .2399911 othrace | .0526882 .2235304 married | .5086022 .500195 ------------------------------------------- . /* test the difference between with parents group and without parents group */ > foreach var in bmi withkid uninsured smoke educ age employed black hispanic othrace married{; 2. reg `var' with_p if !male, robust; 3. reg `var' with_p if male, robust; 4. }; Linear regression Number of obs = 2725 F( 1, 2723) = 68.61 Prob > F = 0.0000 R-squared = 0.0233 Root MSE = 5.3804 ------------------------------------------------------------------------------ | Robust bmi | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -1.785613 .2155713 -8.28 0.000 -2.208313 -1.362913 _cons | 25.62744 .1275306 200.95 0.000 25.37738 25.87751 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 60.84 Prob > F = 0.0000 R-squared = 0.0262 Root MSE = 4.6178 ------------------------------------------------------------------------------ | Robust bmi | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -1.538216 .1972039 -7.80 0.000 -1.924935 -1.151497 _cons | 26.55467 .1260706 210.63 0.000 26.30744 26.80189 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 41.31 Prob > F = 0.0000 R-squared = 0.0148 Root MSE = .49642 ------------------------------------------------------------------------------ | Robust withkid | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.1305901 .0203173 -6.43 0.000 -.1704289 -.0907513 _cons | .5338346 .0115649 46.16 0.000 .5111577 .5565115 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 17.66 Prob > F = 0.0000 R-squared = 0.0075 Root MSE = .46474 ------------------------------------------------------------------------------ | Robust withkid | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.082281 .0195799 -4.20 0.000 -.1206774 -.0438845 _cons | .3532487 .013068 27.03 0.000 .3276221 .3788752 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 36.19 Prob > F = 0.0000 R-squared = 0.0112 Root MSE = .38353 ------------------------------------------------------------------------------ | Robust uninsured | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0877836 .0145915 -6.02 0.000 -.1163952 -.059172 _cons | .2094522 .0094336 22.20 0.000 .1909545 .2279499 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 41.41 Prob > F = 0.0000 R-squared = 0.0169 Root MSE = .43244 ------------------------------------------------------------------------------ | Robust uninsured | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.1153678 .0179273 -6.44 0.000 -.1505234 -.0802121 _cons | .3024645 .012558 24.09 0.000 .2778381 .327091 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 20.74 Prob > F = 0.0000 R-squared = 0.0069 Root MSE = .42099 ------------------------------------------------------------------------------ | Robust smoke | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0754114 .016557 -4.55 0.000 -.107877 -.0429458 _cons | .2561762 .0101198 25.31 0.000 .2363328 .2760195 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 5.57 Prob > F = 0.0183 R-squared = 0.0024 Root MSE = .45796 ------------------------------------------------------------------------------ | Robust smoke | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0457764 .019391 -2.36 0.018 -.0838023 -.0077505 _cons | .3188947 .0127418 25.03 0.000 .2939078 .3438816 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 3.45 Prob > F = 0.0632 R-squared = 0.0010 Root MSE = 2.1959 ------------------------------------------------------------------------------ | Robust educ | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.1501594 .0807955 -1.86 0.063 -.308586 .0082673 _cons | 13.41783 .0551437 243.33 0.000 13.3097 13.52596 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 13.96 Prob > F = 0.0002 R-squared = 0.0053 Root MSE = 2.237 ------------------------------------------------------------------------------ | Robust educ | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.3332675 .0891847 -3.74 0.000 -.5081596 -.1583754 _cons | 13.15907 .0694457 189.49 0.000 13.02289 13.29526 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 1381.41 Prob > F = 0.0000 R-squared = 0.3191 Root MSE = 3.1587 ------------------------------------------------------------------------------ | Robust age | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -4.646964 .1250284 -37.17 0.000 -4.892125 -4.401804 _cons | 25.70838 .075569 340.20 0.000 25.5602 25.85656 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 1220.59 Prob > F = 0.0000 R-squared = 0.3378 Root MSE = 3.139 ------------------------------------------------------------------------------ | Robust age | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -4.55612 .13041 -34.94 0.000 -4.811855 -4.300384 _cons | 25.57655 .0907814 281.74 0.000 25.39853 25.75457 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 0.02 Prob > F = 0.8785 R-squared = 0.0000 Root MSE = .48506 ------------------------------------------------------------------------------ | Robust employed | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0030556 .0199864 -0.15 0.879 -.0422455 .0361344 _cons | .622986 .0112354 55.45 0.000 .6009553 .6450168 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 87.96 Prob > F = 0.0000 R-squared = 0.0402 Root MSE = .42946 ------------------------------------------------------------------------------ | Robust employed | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.1785565 .0190382 -9.38 0.000 -.2158906 -.1412224 _cons | .8140403 .0106374 76.53 0.000 .7931804 .8349003 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 42.71 Prob > F = 0.0000 R-squared = 0.0124 Root MSE = .33624 ------------------------------------------------------------------------------ | Robust black | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0808803 .012376 -6.54 0.000 -.1051475 -.056613 _cons | .1573577 .0084418 18.64 0.000 .1408047 .1739107 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 39.99 Prob > F = 0.0000 R-squared = 0.0152 Root MSE = .30193 ------------------------------------------------------------------------------ | Robust black | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0763642 .0120763 -6.32 0.000 -.1000459 -.0526824 _cons | .1344287 .0093261 14.41 0.000 .1161402 .1527172 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 28.79 Prob > F = 0.0000 R-squared = 0.0088 Root MSE = .3404 ------------------------------------------------------------------------------ | Robust hispanic | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0687557 .0128138 -5.37 0.000 -.0938814 -.04363 _cons | .1568206 .0084301 18.60 0.000 .1402906 .1733506 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 96.88 Prob > F = 0.0000 R-squared = 0.0349 Root MSE = .33982 ------------------------------------------------------------------------------ | Robust hispanic | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.1313908 .0133489 -9.84 0.000 -.1575682 -.1052134 _cons | .1926811 .0107831 17.87 0.000 .1715353 .2138269 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 23.69 Prob > F = 0.0000 R-squared = 0.0066 Root MSE = .23848 ------------------------------------------------------------------------------ | Robust othrace | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0416689 .0085605 -4.87 0.000 -.0584547 -.0248831 _cons | .0741139 .0060729 12.20 0.000 .0622058 .0860219 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 2.53 Prob > F = 0.1120 R-squared = 0.0011 Root MSE = .24139 ------------------------------------------------------------------------------ | Robust othrace | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | -.0160198 .010077 -1.59 0.112 -.0357809 .0037413 _cons | .068708 .0069159 9.93 0.000 .0551459 .0822701 ------------------------------------------------------------------------------ Linear regression Number of obs = 2725 F( 1, 2723) = 9.79 Prob > F = 0.0018 R-squared = 0.0035 Root MSE = .49632 ------------------------------------------------------------------------------ | Robust married | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | .0635426 .0203104 3.13 0.002 .0237173 .1033679 _cons | .5343716 .0115641 46.21 0.000 .5116964 .5570469 ------------------------------------------------------------------------------ Linear regression Number of obs = 2269 F( 1, 2267) = 1.86 Prob > F = 0.1723 R-squared = 0.0008 Root MSE = .49994 ------------------------------------------------------------------------------ | Robust married | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- with_p | .0291399 .0213432 1.37 0.172 -.0127143 .070994 _cons | .4794623 .0136585 35.10 0.000 .4526777 .5062468 ------------------------------------------------------------------------------ . log close; log: G:\Yu\research\Health Economics\2010\table6.log log type: text closed on: 16 Jun 2010, 00:06:42 --------------------------------------------------------------------------------------------------------------------------------------------------