Hello Statalisters,

I'm having an issue obtaining the table that I want using collect with mi estimate and this issue only comes up with factor variables and not continuous ones.

I run the following :

Code:
collect clear
collect TR=_r_b SE=_r_se Lower=_r_lb Upper=_r_ub Pvalue=_r_p, ///
    :streg ib1.pbq_sex,vce(cluster team) dist(loglogistic) nolog tr
collect dims
collect levelsof result
collect style cell result, nformat(%6.3f)
collect layout (colname) (result)
output is shown below:

Code:
. collect clear

. collect TR=_r_b SE=_r_se Lower=_r_lb Upper=_r_ub Pvalue=_r_p, ///
>         :streg ib1.pbq_sex,vce(cluster team) dist(loglogistic) nolog tr

         Failure _d: injuryr1==1 2 3 9
   Analysis time _t: (enddate-origin)
             Origin: time rtpdate
  Exit on or before: time enddate

Loglogistic AFT regression

No. of subjects =    15,648                             Number of obs = 15,648
No. of failures =     2,979
Time at risk    = 1,213,389
                                                        Wald chi2(1)  =   5.28
Log pseudolikelihood = -6890.3172                       Prob > chi2   = 0.0215

                                 (Std. err. adjusted for 313 clusters in team)
------------------------------------------------------------------------------
             |               Robust
          _t | Time ratio   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
     pbq_sex |
     Female  |    1.77584   .4437184     2.30   0.022     1.088226    2.897933
       _cons |   163.0145   11.89825    69.79   0.000     141.2856    188.0851
-------------+----------------------------------------------------------------
    /lngamma |  -.9076884   .1276073    -7.11   0.000    -1.157794   -.6575827
-------------+----------------------------------------------------------------
       gamma |   .4034558   .0514839                      .3141784    .5181022
------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation to time ratios.
Note: _cons estimates baseline time.

. collect dims

Collection dimensions
Collection: default
-----------------------------------------
                   Dimension   No. levels
-----------------------------------------
Layout, style, header, label
                      cmdset   1         
                       coleq   3         
                     colname   5         
           colname_remainder   1         
                     pbq_sex   2         
               program_class   2         
                      result   56        
                 result_type   3         
                     rowname   1         

Style only
                border_block   4         
                   cell_type   4         
-----------------------------------------

. collect levelsof result

Collection: default
 Dimension: result
    Levels: Lower N N_clust N_fail N_sub Pvalue SE TR Upper _r_b _r_ci _r_df _r_lb _r_p _r_se _r_ub _r_z
            _r_z_abs chi2 chi2type clustvar cmd cmd2 cmdline converged dead depvar df_m frm2 gamma ic k
            k_aux k_dv k_eq k_eq_model ll ll_0 ml_method opt p predict predict_sub properties rank rank0
            rc risk stcurve t0 technique title user vce vcetype which

. collect style cell result, nformat(%6.3f)

. collect layout (colname) (result)

Collection: default
      Rows: colname
   Columns: result
   Table 1: 4 x 5

-------------------------------------------------
          |      TR     SE   Lower   Upper Pvalue
----------+--------------------------------------
Female    |   1.776  0.444   1.088   2.898  0.022
Male      |   1.000  0.000       .       .      .
lngamma   |  -0.908  0.128  -1.158  -0.658  0.000
Intercept | 163.014 11.898 141.286 188.085  0.000
-------------------------------------------------

.

this is fine i can work with that table.

The issue arises when I am trying to use this in combination with mi estimate:
Code:
. collect clear

. collect _r_b _r_se _r_lb _r_ub _r_p ///
>         :mi estimate,dots eform(Time ratio) cmdok:streg ib1.pbq_sex,vce(cluster team) dist(loglogistic) n
> olog

Imputations (50):
  .........10.........20.........30.........40.........50 done

Multiple-imputation estimates                   Imputations       =         50
Loglogistic AFT regression                      Number of obs     =        448
                                                Average RVI       =     0.0000
                                                Largest FMI       =     0.0000
DF adjustment:   Large sample                   DF:     min       =   4.84e+61
                                                        avg       =   4.84e+61
                                                        max       =          .
Model F test:       Equal FMI                   F(   1,      .)   =       2.23
Within VCE type:       Robust                   Prob > F          =     0.1353

                                (Within VCE adjusted for 313 clusters in team)
------------------------------------------------------------------------------
          _t | Time ratio   Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     pbq_sex |
     Female  |    1.43824   .3499714     1.49   0.135     .8927003    2.317164
       _cons |   174.1712   12.62802    71.17   0.000     151.0989    200.7666
-------------+----------------------------------------------------------------
    /lngamma |  -.8595957    .112937    -7.61   0.000    -1.080948   -.6382433
-------------+----------------------------------------------------------------
       gamma |   .4233332     .04781                      .3392737    .5282196
------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation to time ratios.
Note: _cons estimates baseline time.

. collect dims

Collection dimensions
Collection: default
-----------------------------------------
                   Dimension   No. levels
-----------------------------------------
Layout, style, header, label
                      cmdset   1         
                       coleq   2         
                     colname   9         
           colname_remainder   1         
                     pbq_sex   2         
               program_class   1         
                      result   99        
                 result_type   3         
                       roweq   2         
                     rowname   5         

Style only
                border_block   4         
                   cell_type   4         
-----------------------------------------

. collect levelsof result

Collection: default
 Dimension: result
    Levels: B_mi Cns_mi F_mi M_mi N N_clust N_clust_mi N_fail N_max_mi N_mi N_min_mi N_sub N_sub_mi V_mi
            W_mi _dfnote_mi _predict_mi _sortseed_mi _sortseedcmd_mi b_mi chi2 chi2type cilevel_mi
            clustvar cmd cmd_mi cmdline cmdline_mi consonly converged converged_cons crittype dead depvar
            df_avg_mi df_c_mi df_m df_m_mi df_max_mi df_mi df_min_mi df_r_mi dfadjust_mi diparm1 ecmd2_mi
            ecmd_mi esampvary_mi fmi_max_mi fmi_mi frm2 gamma ic k k_autoCns k_aux k_dv k_eq k_eq_model
            k_eq_model_mi k_exp_mi ll ll_0 m_est_mi m_mi marginsfootnote marginsprop mcerror_mi mi
            ml_method modeltest_mi noconstant opt p p_mi pise_mi predict_sub prefix_mi rank rank0 rc
            rc_mi re_mi reparm_rc_mi risk rvi_avg_F_mi rvi_avg_mi rvi_mi singularHmethod stcurve t0
            technique title title_mi ufmi_mi user vce vcetype which wvce_mi

. collect style cell result, nformat(%6.3f)

. collect layout (colname) (result)

Collection: default
      Rows: colname
   Columns: result

Your layout specification does not identify any items.
I notice that the _r_b series are not in the result dimensions with mi estimates using a factor variable but when I use a continuous variable with mi estimate they are indeed there and I get the table that I want...

I'd love to know what I'm doing wrong.

Regards,

Jean-Michel