Hello,

I am running the ordered logit regression to predict eh041, by regression on the variables aa001, aa004, ba016, ca001, ea104, eb001, eb002, ec023, and dummy.

My question is: Is it better to report the coefficients, standard errors, and p-values for each individual predictor, or for the entire model (if so, which statistics to report?)?

Example of the dataset:
Code:
input long id int year byte(ca001 aa001) float aa004 byte(eb001 eb002) float(ea104 ec023) byte(eh041 ba016) int(dummy)
11001 2004 1 1 60 0 1   10 3 2 4 0
11001 2006 . .  . . .    . . . . 1
11002 2004 . 2 65 . .    . . . 4 0
11002 2006 . .  . . .    . . . . 1
25601 2004 1 1 50 0 1   36 5 2 6 0
25601 2006 1 1 52 0 1   36 4 1 6 1
Command for ordered logit regression:
Code:
ologit eh041 aa001 aa004 ba016 ca001 ea104 eb001 eb002 ec023 dummy
Output:
Code:
note: ca001 omitted because of collinearity
Iteration 0:   log likelihood = -5928.1906  
Iteration 1:   log likelihood = -5880.5609  
Iteration 2:   log likelihood = -5880.4552  
Iteration 3:   log likelihood = -5880.4552  

Ordered logistic regression                     Number of obs     =      6,312
                                                LR chi2(8)        =      95.47
                                                Prob > chi2       =     0.0000
Log likelihood = -5880.4552                     Pseudo R2         =     0.0081

------------------------------------------------------------------------------------
             eh041 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
             aa001 |  -.3323744   .0608015    -5.47   0.000    -.4515431   -.2132056
             aa004 |  -.0066495   .0024361    -2.73   0.006    -.0114241   -.0018748
             ba016 |   .0874215      .0311     2.81   0.005     .0264666    .1483763
             ca001 |          0  (omitted)
             ea104 |  -.0065987   .0030108    -2.19   0.028    -.0124998   -.0006976
             eb001 |   .0052226   .0671317     0.08   0.938    -.1263531    .1367982
             eb002 |  -.2247139   .0795934    -2.82   0.005    -.3807141   -.0687136
             ec023 |  -.2138397   .0323412    -6.61   0.000    -.2772272   -.1504521
             dummy |   .0544896   .0502734     1.08   0.278    -.0440444    .1530237
-------------------+----------------------------------------------------------------
             /cut1 |  -2.209866   .2457687                     -2.691564   -1.728168
             /cut2 |   .8122446   .2445497                       .332936    1.291553
             /cut3 |   3.017259   .2680799                      2.491832    3.542686
------------------------------------------------------------------------------------