Dear Statalist,

I have a question concerning the a logistic regression with panel data. I have a panel dataset containing only 61 observations and 12 groups. My dependent variable is whether sexual violence has happened in a conflict or not. I ran a regression using xtlogit and everything worked perfectly fine, but I discovered that the probability of the LR test at the bottom is 1. Now, I do not know whether I have to change anything or what to do with it? I looked it up in the Stata Manual and it says, that this test compares the pooled estimator (logit) with the panel estimator, but what does that mean?
I am working with version 15 in Stata.

This is my code:
Code:
xtlogit sexual_violence_bin women_share GenderGap P3_Human_Rights polity loggdp Population i.conflict_activity year_count region, re 

Fitting comparison model:

Iteration 0:   log likelihood = -33.961598  
Iteration 1:   log likelihood = -17.415634  
Iteration 2:   log likelihood = -14.828786  
Iteration 3:   log likelihood = -12.420276  
Iteration 4:   log likelihood = -11.272802  
Iteration 5:   log likelihood = -11.182178  
Iteration 6:   log likelihood = -11.180721  
Iteration 7:   log likelihood =  -11.18072  

Fitting full model:

tau =  0.0     log likelihood =  -11.18072
tau =  0.1     log likelihood = -11.332501

Iteration 0:   log likelihood = -11.332501  
Iteration 1:   log likelihood = -11.181432  
Iteration 2:   log likelihood = -11.180724  
Iteration 3:   log likelihood =  -11.18072  
Iteration 4:   log likelihood =  -11.18072  

Random-effects logistic regression              Number of obs     =         53
Group variable: missionid                       Number of groups  =         12

Random effects u_i ~ Gaussian                   Obs per group:
                                                              min =          2
                                                              avg =        4.4
                                                              max =          6

Integration method: mvaghermite                 Integration pts.  =         12

                                                Wald chi2(10)     =       5.58
Log likelihood  =  -11.18072                    Prob > chi2       =     0.8496

-------------------------------------------------------------------------------------
sexual_violence_bin |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
        women_share |  -34.39814   47.97645    -0.72   0.473    -128.4303    59.63398
          GenderGap |   40.76391   25.25293     1.61   0.106    -8.730913    90.25874
    P3_Human_Rights |   4.845226   2.226682     2.18   0.030     .4810104    9.209442
             polity |  -6.039683   3.102269    -1.95   0.052    -12.12002    .0406531
             loggdp |  -1.842643   1.797294    -1.03   0.305    -5.365273    1.679988
         Population |   1.49e-08   2.06e-08     0.72   0.471    -2.55e-08    5.52e-08
                    |
  conflict_activity |
                 2  |    2.31902   3.866796     0.60   0.549    -5.259761    9.897802
                 3  |   6.933563   4.103001     1.69   0.091    -1.108171     14.9753
                    |
         year_count |  -.8181246   .4552427    -1.80   0.072    -1.710384    .0741347
             region |  -4.842108   2.928383    -1.65   0.098    -10.58163    .8974175
              _cons |   .0909244   26.32624     0.00   0.997    -51.50757    51.68941
--------------------+----------------------------------------------------------------
           /lnsig2u |  -17.75879   1554.457                     -3064.439    3028.921
--------------------+----------------------------------------------------------------
            sigma_u |   .0001392   .1082125                             0           .
                rho |   5.89e-09   9.16e-06                             0           .
-------------------------------------------------------------------------------------
LR test of rho=0: chibar2(01) = 0.00                   Prob >= chibar2 = 1.000
Thank you so much for your help in advance