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  • How to graph results of logistic regression in Stata?

    Dear all,

    I am trying to examine the relationship between education and a woman’s probability of getting married, using a discrete time logistic regression model. The dependent variable is married (=1 or 0). For controls, I have a categorical variable for the individual’s own level of education, edu_cat (where 0 is no education, 1 and 2 are primary and secondary schooling respectively), and a bunch of other predictors. My Stata code and results are below.

    Code:
    . logistic married pyear pyearsq i.edu_cat i.bict muslim father_5andaboveeduc mother_5andaboveeduc hh_lowinc i.rural_div [pw= popweight]
     
    Logistic regression                             Number of obs     =     30,336
                                                    Wald chi2(16)     =    3150.08
                                                    Prob > chi2       =     0.0000
    Log pseudolikelihood = -1.856e+08               Pseudo R2         =     0.1996
     
    --------------------------------------------------------------------------------------
                         |               Robust
                 married | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
    ---------------------+----------------------------------------------------------------
                   pyear |   5.214708   .3749294    22.97   0.000     4.529288    6.003853
                 pyearsq |   .9621039   .0020803   -17.87   0.000     .9580353    .9661898
                         |
                 edu_cat |
                      1  |   .9944425   .0526095    -0.11   0.916     .8964955    1.103091
                      2  |   .7840981   .0457952    -4.16   0.000      .699288    .8791941
                         |
                    bict |
    birthcohort 1976-86  |   1.072139   .0569778     1.31   0.190     .9660838    1.189837
    birthcohort 1987-97  |   1.036028   .0625042     0.59   0.557     .9204877    1.166071
                         |
                  muslim |   1.299013   .0886869     3.83   0.000     1.136318    1.485003
    father_5andaboveeduc |   .8964348   .0458894    -2.14   0.033     .8108581    .9910432
    mother_5andaboveeduc |   .8650096   .0561416    -2.23   0.025     .7616852    .9823502
               hh_lowinc |   1.054659   .0639445     0.88   0.380     .9364904    1.187738
                         |
               rural_div |
                Barisal  |   1.185689   .1008533     2.00   0.045     1.003619     1.40079
             Chittagong  |    1.04448   .0626355     0.73   0.468     .9286565    1.174749
                 Khulna  |   1.447291   .1105905     4.84   0.000     1.245988    1.681117
               Rajshahi  |   1.298267    .090639     3.74   0.000     1.132236    1.488644
                Rangpur  |   1.429192   .1046735     4.88   0.000     1.238081    1.649804
                 Sylhet  |   .7301493   .0478659    -4.80   0.000     .6421108    .8302585
                         |
                   _cons |   1.47e-08   8.71e-09   -30.37   0.000     4.58e-09    4.70e-08
    --------------------------------------------------------------------------------------
    I am presenting my analysis at a meeting, and would like to make my results more visually engaging, thereby presenting graphs rather than a bunch of regression tables. I was just wondering what command to use if I want to graph the relationship between the outcome variable, married, (which is binary) and the dependent variable, edu_cat, which is categorical.

    Thank you!

    Monzur

  • #2
    I suggest you use the - margins - followed by the - marginsplot - command.
    Best regards,

    Marcos

    Comment


    • #3
      It worked, thank you very much!

      Best,

      Monzur

      Comment


      • #4
        I like to present regression model results as forest plots. See for example https://www.ctspedia.org/do/view/CTS...ClinAEGraph001 (click to enlarge). It's a way to visualize the effects and their precision, as well as their direction and significance, all at once. For logit models, this can be ORs, with a vertical line at 1.0.

        hth,
        Jeph
        '

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