Announcement

Collapse
No announcement yet.
X
  • Filter
  • Time
  • Show
Clear All
new posts

  • bootstrap: insufficient observations to compute bootstrap standard errors

    I don't know the exact reason. Can anyone help me out? Here is the data and code:
    Code:
    * Example generated by -dataex-. To install: ssc install dataex
    clear
    input double(dv id serial) float(iv med mod1 newid)
      4  1 1     .12499996    .5486109 -.05694437  1
      4  1 2    -.07500005  -.17361127 -.05694437  1
      4  1 3    -.07500005    .5486109 -.05694437  1
    3.8  1 4    -.07500005  -.06250016 -.05694437  1
      4  1 5    -.07500005    .3263887 -.05694437  1
      3  1 6    -.07500005   -.3958335 -.05694437  1
      4  1 7          .325   -.3958335 -.05694437  1
      4  1 8    -.07500005   -.3958335 -.05694437  1
    3.2  2 1         1.725   -.4375001  .14305563  2
    3.7  2 2          .725   -.3819445  .14305563  2
    3.7  2 3     -.6750001  .006944391  .14305563  2
    3.4  2 4    -.07500005    .2291666  .14305563  2
    3.3  2 5        -1.075  -.54861116  .14305563  2
      3  2 6          .325    .2291666  .14305563  2
    4.7  2 7    -.27500004    .4513888  .14305563  2
      5  2 8     -.6750001    .4513888  .14305563  2
      4  3 1         -.125 -.013888836  -.3569444  3
    3.5  3 2          .075 -.013888836  -.3569444  3
    3.8  3 3         -.125 -.013888836  -.3569444  3
    3.6  3 4         -.125   .09722228  -.3569444  3
    3.8  3 5          .075 -.013888836  -.3569444  3
      4  3 6          .075 -.013888836  -.3569444  3
    3.8  3 7          .075 -.013888836  -.3569444  3
      4  3 8          .075 -.013888836  -.3569444  3
    3.2  4 1    -.17142864 -.007936531  -.4569444  4
    3.7  4 2     -.7714286   .04761903  -.4569444  4
    2.7  4 3     .02857137  -.06349209  -.4569444  4
    2.2  4 4      .4285714  -.11904764  -.4569444  4
    2.4  4 5      .6285714   .10317458  -.4569444  4
    2.9  4 6     .22857137    .3253968  -.4569444  4
      .  4 7             .           .  -.4569444  4
    3.8  4 8     -.3714286   -.2857143  -.4569444  4
    3.9  5 1    .025000047   .58333325 -.15694436  5
    4.3  5 2    -.17499995   .02777767 -.15694436  5
    4.1  5 3    -.17499995    .4166666 -.15694436  5
    3.4  5 4    .025000047  -.25000012 -.15694436  5
    3.5  5 5          .425   -.3611112 -.15694436  5
    3.8  5 6     .22500005  -.19444455 -.15694436  5
    3.1  5 7    -.17499995  -.25000012 -.15694436  5
    4.3  5 8    -.17499995   .02777767 -.15694436  5
      4  6 1      .7000001  -.08333354  .14305563  6
    4.2  6 2      .3000001     .472222  .14305563  6
      4  6 3      .1000001  .027777566  .14305563  6
    3.6  6 4     -.2999999  -.08333354  .14305563  6
    3.3  6 5     -.2999999  -.08333354  .14305563  6
    3.8  6 6     -.2999999   -.1388891  .14305563  6
    3.3  6 7      .1000001  -.08333354  .14305563  6
    3.3  6 8     -.2999999  -.02777799  .14305563  6
    3.8  7 1     -.0999999   .06250016  .14305563  7
    3.5  7 2     -.0999999    .3402779  .14305563  7
    3.3  7 3     -.0999999   .11805572  .14305563  7
    2.8  7 4     -.0999999   -.1041665  .14305563  7
      3  7 5      .3000001   -.1041665  .14305563  7
      3  7 6      .1000001   -.1041665  .14305563  7
    3.2  7 7      .1000001   -.1041665  .14305563  7
      3  7 8     -.0999999   -.1041665  .14305563  7
      .  8 1             .           .   .4430556  8
      .  8 2             .           .   .4430556  8
    4.5  8 3    .033333253    -.111111   .4430556  8
    3.6  8 4     -.3666667    -.111111   .4430556  8
    3.4  8 5    .033333253  -.05555545   .4430556  8
    3.1  8 6    -.16666675   .22222233   .4430556  8
    3.4  8 7     .43333325   .16666678   .4430556  8
    3.6  8 8    .033333253    -.111111   .4430556  8
    4.1  9 1     .12500003    .3680556 -.05694437  9
    4.6  9 2     .12500003   .47916675 -.05694437  9
    4.5  9 3    -.27499998  -2.1319444 -.05694437  9
      4  9 4     .12500003   .14583342 -.05694437  9
    4.5  9 5     .12500003   .14583342 -.05694437  9
      4  9 6    -.27499998    .3680556 -.05694437  9
    4.5  9 7     .12500003   .25694454 -.05694437  9
    4.5  9 8    -.07499997    .3680556 -.05694437  9
    3.4 10 1            .2           0   .8430556 10
    3.5 10 2            .2           0   .8430556 10
    3.7 10 3            .2           0   .8430556 10
      3 10 4             0           0   .8430556 10
    3.3 10 5            .2           0   .8430556 10
    3.6 10 6           -.8           0   .8430556 10
      3 10 7             0           0   .8430556 10
      3 10 8             0           0   .8430556 10
    3.8 11 1            .8           0  .24305563 11
    3.8 11 2    -.20000005           0  .24305563 11
    3.4 11 3    -.20000005           0  .24305563 11
    3.8 11 4    -.20000005           0  .24305563 11
    3.6 11 5 -4.768372e-08           0  .24305563 11
      4 11 6    -.20000005           0  .24305563 11
    3.6 11 7 -4.768372e-08           0  .24305563 11
    3.4 11 8 -4.768372e-08           0  .24305563 11
    4.1 12 1          -.75           0 -.05694437 12
    3.3 12 2          -.55           0 -.05694437 12
    3.8 12 3           .25           0 -.05694437 12
    3.9 12 4          -.75           0 -.05694437 12
    3.9 12 5          -.35           0 -.05694437 12
    3.6 12 6           .65           0 -.05694437 12
      3 12 7           .25           0 -.05694437 12
    4.3 12 8          1.25           0 -.05694437 12
      3 13 1             0 -.009259198  -.6569444 13
      3 13 2             0 -.009259198  -.6569444 13
      3 13 3             0 -.064814754  -.6569444 13
      3 13 4             0 -.009259198  -.6569444 13
    end
    xtset id serial
    set seed 10000
    capture program drop MoDMed
    program define MoDMed, rclass
     quietly summarize mod1
        return list
        global m=r(mean)
        global sd=r(sd)
    mixed med  l.iv mod1 cl.iv#c.mod1 || id: l.iv, var cov(exc) iter(50)
        return scalar al=(_b[med:L.iv]+_b[med:cL.iv#c.mod1]*($m-$sd))
        return scalar ah=(_b[med:L.iv]+_b[med:cL.iv#c.mod1]*($m+$sd))
        
    mixed dv  med l.iv   || id: l.iv med, var  cov(exc) iter(50)
        return scalar b=(_b[dv:med])
    
    end
    
    bootstrap indL=(r(al)*r(b)) indH=(r(ah)*r(b)) diff=(r(ah)*r(b)-r(al)*r(b)), reps(50) reject(e(converged)!=1) cluster(id) idcluster(newid) group(serial): MoDMed
    estat bootstrap
    program drop MoDMed
Working...
X