在Stata中使用用户编写的命令箱更改估计效果
我在Stata中使用用户编写的命令在Stata中使用用户编写的命令箱更改估计效果,stata,Stata,我在Stata中使用用户编写的命令cost，查看模型中变量的估计变化 在运行 regress age allelecount gender htn_g dm_g lipid_g i.hx_smoking b_bmi hx_med_asa if cadhx2==0 我运行cost命令 chest allelecount, backward nograph 但我只得到一个变量的输出 chest allelecount, backward Change-in-estimate regress r
costregress age allelecount gender htn_g dm_g lipid_g i.hx_smoking b_bmi hx_med_asa if cadhx2==0
costchest allelecount, backward nograph
chest allelecount, backward
Change-in-estimate
regress regression. Outcome: age
number of obs = 476 Exposure: allelecount
----------------------------------------------------------
Variables |
removed | Coef. [95% Conf. Interval] Change, %
----------+-----------------------------------------------
Adj.All | -0.3691 -0.6819 -0.0564
-lipid_g | -0.3688 -0.6804 -0.0571 -0.0996
----------------------------------------------------------
有人能解释一下吗？使用Stata的自动数据，我发现没有问题：
sysuse auto
regress price mpg rep78 headroom
Source | SS df MS Number of obs = 69
-------------+------------------------------ F( 3, 65) = 7.51
Model | 148497605 3 49499201.8 Prob > F = 0.0002
Residual | 428299354 65 6589220.82 R-squared = 0.2575
-------------+------------------------------ Adj R-squared = 0.2232
Total | 576796959 68 8482308.22 Root MSE = 2566.9
------------------------------------------------------------------------------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
mpg | -289.3462 62.53921 -4.63 0.000 -414.2456 -164.4467
rep78 | 670.8971 343.5213 1.95 0.055 -15.16242 1356.957
headroom | -300.0293 398.0516 -0.75 0.454 -1094.993 494.9346
_cons | 10921.33 2153.003 5.07 0.000 6621.487 15221.17
chest mpg,backward
Change-in-estimate
regress regression. Outcome: price
number of obs = 69 Exposure: mpg
----------------------------------------------------------
Variables |
removed | Coef. [95% Conf. Interval] Change, %
----------+-----------------------------------------------
Adj.All | -289.3462 -411.9208 -166.7715
-headroom | -271.6425 -384.8719 -158.4132 -6.1185
-rep78 | -226.3607 -332.1613 -120.5600 -16.6697
----------------------------------------------------------
使用Stata的自动数据，我发现没有问题：
sysuse auto
regress price mpg rep78 headroom
Source | SS df MS Number of obs = 69
-------------+------------------------------ F( 3, 65) = 7.51
Model | 148497605 3 49499201.8 Prob > F = 0.0002
Residual | 428299354 65 6589220.82 R-squared = 0.2575
-------------+------------------------------ Adj R-squared = 0.2232
Total | 576796959 68 8482308.22 Root MSE = 2566.9
------------------------------------------------------------------------------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
mpg | -289.3462 62.53921 -4.63 0.000 -414.2456 -164.4467
rep78 | 670.8971 343.5213 1.95 0.055 -15.16242 1356.957
headroom | -300.0293 398.0516 -0.75 0.454 -1094.993 494.9346
_cons | 10921.33 2153.003 5.07 0.000 6621.487 15221.17
chest mpg,backward
Change-in-estimate
regress regression. Outcome: price
number of obs = 69 Exposure: mpg
----------------------------------------------------------
Variables |
removed | Coef. [95% Conf. Interval] Change, %
----------+-----------------------------------------------
Adj.All | -289.3462 -411.9208 -166.7715
-headroom | -271.6425 -384.8719 -158.4132 -6.1185
-rep78 | -226.3607 -332.1613 -120.5600 -16.6697
----------------------------------------------------------