Table 5: Model two multivariate logistic regression.
Treat_outcome_4 |
Coef. |
Std. Err. |
z |
P > |z| |
[95% Conf. Interval] |
Treatment - Success
|
(Base outcome) |
|
|
|
|
Failed TypeofTB-1 Registrationgroup-1 ResistancePattern-1 GeneXpert-1 LPA-Rif-1 LPA-H-1 RDST-1 HDST-1 EDST-1 ZDST- -Cons |
-1.825038 -0.0841873 0.0930298 -0.2844209 0.9053925 -0.1876877 -0.1571005 -0.538345 0.3540237 -0.2392338 3.647367
|
1.357333 0.0568274 0.0853065 0.1093212 0.2693812 0.3089199 0.3053129 0.316283 0.3070321 0.2403558 2.85041 |
-1.34 -1.48 1.09 -2.60 3.36 -0.61 -0.51 -1.70 1.15 -1.00 1.28
|
0.179 0.138 0.275 0.009 0.001 0.543 0.607 0.089 0.249 0.320 0.201 |
-4.485361 0.8352848 -0.195567 0.0271925 -0.0741678 0.2602275 -0.4986865 -0.0701552 0.3774151 1.43337 -0.7931595 0.4177842 -0.7555028 0.4413017 -1.158248 0.0815582 -0.2477482 0.9557955 -0.7103225 0.2318549 -1.939335 9.234068
|
Ongoing_Meds TypeofTB-1 Registrationgroup-1 ResistancePattern-1 GeneXpert-1 LPA-Rif-1 LPA-H-1 RDST-1 HDST-1 EDST-1 ZDST- -Cons |
-0.6064315 -0.0125487 0.2517586 -0.1894462 0.5873974 0.3690152 0.7091217 -0.5297356 0.1111455 -0.3336719 -0.1749003 |
1.498924 0.0414727 0.0652931 0.0762573 0.216092 0.2081382 0.2122312 0.2211231 0.2092462 0.1737019 3.064384 |
-0.40 -0.30 3.86 -2.48 2.72 1.77 3.34 -2.40 0.53 -1.92 -0.06 |
0.686 0.762 0.000 0.013 0.007 0.076 0.001 0.017 0.595 0.055 0.954 |
-3.544268 2.331405 -0.0938337 0.0687363 0.1237865 0.3797308 -0.3389077 -0.0399847 0.1638648 1.01093 -0.0389283 0.7769587 0.2931561 1.125087 -0.9631289 -0.0963423 -0.2989696 0.5212606 -0.6741214 0.0067777 -6.180983 5.831182
|
mlogit Treat_outcome_4 TypeofTB_1 Registrationgroup_1 ResistancePattern_1 GeneXpert_1 LPA_Rif_1 LPA_H_1 RDST_1 HDST_1 EDST_1 ZDST_1
Iteration 0:log likelihood = -834.14576; Iteration 1: log likelihood = -789.20785; Iteration 2: log likelihood = -787.94823; Iteration 3: log likelihood = -787.91722; Iteration 4: log likelihood = -787.91714; Iteration 5: log likelihood = -787.91714
Multinomial logistic regression Number of obs =828; LR chi2(20) =92.46; Prob > chi2 = 0.0000; Log likelihood = -787.91714; Pseudo R2 = 0.0554