在Stata中使用均值和qui均值

Question

我有一个输出的代码：

sysuse auto,clear
clear matrix

local vars price weight length
foreach i of local vars{
qui mean `i'
mat `i'=r(table)
scalar mean_`i'=`i'[1,1]
scalar se_`i'=`i'[2,1]
scalar n_`i'=`i'[7,1]+1
scalar sd_`i'=se_`i'*sqrt(n_`i')
mat des_`i'=(n_`i',mean_`i',sd_`i')
mat colnames  des_`i'=Observations Mean SD
mat rownames des_`i'=`i'
mat des_result=nullmat(des_result)\des_`i'
}

estout matrix(des_result,fmt(0 4 4))


---------------------------------------------------
               des_result                          
             Observations         Mean           SD
---------------------------------------------------
price                   .            .            .
weight                  .            .            .
length                  .            .            .
---------------------------------------------------

现在，如果我只将qui mean `i'更改为mean `i'，则有一个输出：

 sysuse auto,clear
    clear matrix

local vars price weight length
foreach i of local vars{
mean `i'
mat `i'=r(table)
scalar mean_`i'=`i'[1,1]
scalar se_`i'=`i'[2,1]
scalar n_`i'=`i'[7,1]+1
scalar sd_`i'=se_`i'*sqrt(n_`i')
mat des_`i'=(n_`i',mean_`i',sd_`i')
mat colnames  des_`i'=Observations Mean SD
mat rownames des_`i'=`i'
mat des_result=nullmat(des_result)\des_`i'
}

estout matrix(des_result,fmt(0 4 4))


---------------------------------------------------
               des_result                          
             Observations         Mean           SD
---------------------------------------------------
price                  74    6165.2568    2949.4959
weight                 74    3019.4595     777.1936
length                 74     187.9324      22.2663
---------------------------------------------------

我想知道为什么当我使用qui时没有得到输出。注意，这与estout无关。这与mean有关。

Answer 1

我不使用estout (SSC/SJ)，但这表明(正如其他人所报告的)我完全没有复制所报告的问题，即当应用quietly时，所需结果的矩阵是空的：

. about 

Stata/SE 13.1 for Windows (64-bit x86-64)
Revision 03 Jul 2014
Copyright 1985-2013 StataCorp LP

编辑了当地和个人详细资料

. sysuse auto,clear
(1978 Automobile Data)

. clear matrix

. local vars price weight length
. foreach i of local vars{
2. qui mean `i'
3. mat `i'=r(table)
4. scalar mean_`i'=`i'[1,1]
5. scalar se_`i'=`i'[2,1]
6. scalar n_`i'=`i'[7,1]+1
7. scalar sd_`i'=se_`i'*sqrt(n_`i')
8. mat des_`i'=(n_`i',mean_`i',sd_`i')
9. mat colnames  des_`i'=Observations Mean SD
10. mat rownames des_`i'=`i'
11. mat des_result=nullmat(des_result)\des_`i'
12. }


. mat li des_result 

 des_result[3,3]
        Observations          Mean            SD
 price            74     6165.2568     2949.4959
 weight           74     3019.4595     777.19357
 length           74     187.93243      22.26634