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        name:  <unnamed>
         log:  Z:\PUBLIC_web\Stataworkshops\Postfiles\jackknife_postfile.smcl
    log type:  smcl
   opened on:  21 Nov 2014, 10:11:30
  

 1 . do "Z:\PUBLIC_web\Stataworkshops\Postfiles\jackknife postfile.do"
  

Markdoc demo

Use the automobile data set. Demonstrate the jackknife command.

 2 . sysuse auto
  (1978 Automobile Data)
  

 3 . regress price mpg weight foreign
  
        Source |       SS       df       MS              Number of obs =      74
  -------------+------------------------------           F(  3,    70) =   23.29
         Model |   317252881     3   105750960           Prob > F      =  0.0000
      Residual |   317812515    70  4540178.78           R-squared     =  0.4996
  -------------+------------------------------           Adj R-squared =  0.4781
         Total |   635065396    73  8699525.97           Root MSE      =  2130.8
  
  ------------------------------------------------------------------------------
         price |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
  -------------+----------------------------------------------------------------
           mpg |    21.8536   74.22114     0.29   0.769    -126.1758     169.883
        weight |   3.464706    .630749     5.49   0.000     2.206717    4.722695
       foreign |    3673.06   683.9783     5.37   0.000     2308.909    5037.212
         _cons |  -5853.696   3376.987    -1.73   0.087    -12588.88    881.4934
  ------------------------------------------------------------------------------
  

 4 . jackknife coef=_b[mpg]: regress price mpg weight foreign
  (running regress on estimation sample)
  
  Jackknife replications (74)
  ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 

 5 . .................................................    50

 6 . .......................
  
  Linear regression                               Number of obs      =        74
                                                  Replications       =        74
  
        command:  regress price mpg weight foreign
           coef:  _b[mpg]
            n():  e(N)
  
  ------------------------------------------------------------------------------
               |              Jackknife
               |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
  -------------+----------------------------------------------------------------
          coef |    21.8536   87.57669     0.25   0.804    -152.6865    196.3937
  ------------------------------------------------------------------------------
  

Produce the same results using postfile.

 7 . postfile coeffs b se using "coeffs.dta", replace
  (note: file coeffs.dta not found)
  

 8 . forvalues i = 1/74 {
    2.         quietly regress price mpg weight foreign if _n~=`i'
    3.         local b _b[mpg]
    4.         local se _se[mpg]
    5.         post coeffs (`b') (`se')
    6.         }
  

 9 . postclose coeffs
  

10 . use "coeffs.dta", clear
  

11 . summarize b se
  
      Variable |       Obs        Mean    Std. Dev.       Min        Max
  -------------+--------------------------------------------------------
             b |        74    21.87022    10.32004  -45.60361    44.3121
            se |        74    74.78354    1.872273   69.52323   87.14951
  

12 . ci se
  
      Variable |        Obs        Mean    Std. Err.       [95% Conf. Interval]
  -------------+---------------------------------------------------------------
            se |         74    74.78354    .2176474        74.34977    75.21732
  
  end of do-file
  

13 . log close
        name:  <unnamed>
         log:  Z:\PUBLIC_web\Stataworkshops\Postfiles\jackknife_postfile.smcl
    log type:  smcl
   closed on:  21 Nov 2014, 10:12:36
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