Hello,

I am trying to use bootstrapping to get a 95% CI for Cohen's d, but the command produces coef. only. No bootstrapping SE, z, p-value, and 95% CI. And I don't get any error messages!
This is very strange because the same codes actually worked without any problem a few weeks ago. I had to revisit the analysis recently so just ran what I wrote before to review, but now, the codes are not working.

FYI, the codes below are a part of what I wrote. And the data is not real data. I used frame since I actually need to handle multiple data sets for this. But it produces the same issue.
Please advise!


Code:
frame reset
frame create sample3
frame sample3 {
    * Example generated by -dataex-. For more info, type help dataex
    clear
    input byte id double(group outcome_t0 outcome_t1 outcome_t2)
    44 2          84.860979 114.87961250000001         41.4992725
    45 1         49.8758465         55.0360915         50.1319545
    46 1  80.74328550000001         77.3736495         81.3353915
    48 1 42.024735500000006          54.970216 57.763051000000004
    49 2          52.415797 56.568540999999996 50.503508499999995
    50 2          48.055269         48.4297725         46.5440855
    58 2         39.3368345          37.401369          37.568878
    60 2         50.3642245 45.998895000000005         46.2884515
    61 2         71.5496255  71.77641600000001  70.61160749999999
    62 2         49.8083935         44.5434755 47.758653499999994
    63 1 57.545792000000006  65.44662199999999          66.445455
    64 2 40.995180000000005         46.6467495         44.6673595
    65 2 52.914714000000004          46.365172          50.470093
    66 2 60.423458499999995                  .                  .
    71 2 50.232740500000006         46.5209385         43.5583465
    end
    label values group group_l
    label def group_l 1 "S", modify
    label def group_l 2 "C", modify
}

capture program drop boot_test
program boot_test, rclass
    version 17
    frame sample3 {
        * getting mean and variance of the outcome at each time point for each group
        sum `1'_t0 if group==1
        local n_grp1_t0=r(N)
        local dep_grp1_t0=r(mean)
        local sd_grp1_t0=r(sd)
        local var_grp1_t0=r(Var)
        sum `1'_t1 if group==1
        local n_grp1_t1=r(N)
        local dep_grp1_t1=r(mean)
        local sd_grp1_t1=r(sd)
        local var_grp1_t1=r(Var)

        
        * difference between two time points
        local dif_grp1_t1t0=`dep_grp1_t1'-`dep_grp1_t0'
        
        * pooled sd
        local sd_pooled_grp1_t1t0=sqrt((`var_grp1_t1'+`var_grp1_t0')/2)
        
        * Cohen's d
        return scalar cohend_grp1_t1t0=`dif_grp1_t1t0'/`sd_pooled_grp1_t1t0'
    }
end

bootstrap r(cohend_grp1_t1t0), reps(1010) seed(11271980): boot_test outcome