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)
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'd love to know what I'm doing wrong.
Regards,
Jean-Michel
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