Differences in number of observations when adding vars in logistic model

[Gadri Cre]

Hi all,

I am currently having trouble deciphering why I am receiving a difference in # of observations whenever I add additional variables to the model. I have attached a document below for reference. Please let me know if you need additional information. Thanks so much in advance!

[Carlo Lazzaro]

Gadri:
how many missing values are detected in -femdom-?

[Gadri Cre]

Gadri:
how many missing values are detected in -femdom-?

Hi Carlo,
Attached is the tabulations/sum of the variables. I'm trying to figure out how to run a model with the exact same observations across the board regardless of how many variables I input. I'm not sure where I am going wrong.

[Gadri Cre]

Gadri:
how many missing values are detected in -femdom-?

Here is the current logit model for reference

[Carlo Lazzaro]

Gadri:
Stata applies the listwise deletion to avoid problems when calculating the VCE matrix.
Therefore, the only way to fix your issue is to avoid having missing values in any of the variables that appear in your logistic regression.
As an aside, please follow the FAQ and use CODE delimiters instead of screenshots when sharing what you typed and what Stata gave you back. Thanks.

[Gadri Cre]

Gadri:
Stata applies the listwise deletion to avoid problems when calculating the VCE matrix.
Therefore, the only way to fix your issue is to avoid having missing values in any of the variables that appear in your logistic regression.
As an aside, please follow the FAQ and use CODE delimiters instead of screenshots when sharing what you typed and what Stata gave you back. Thanks.

Hi Carlo,
Thank you for the information. How would I make sure that the variables I include do not have missing values? That is, what is the easiest or most direct way to do so?

Thank you for letting me know about the CODE delimiters instead of screenshots!

[Carlo Lazzaro]

Gadri:
I usually follow this two-step procedure:

. use "C:\Program Files\Stata18\ado\base\a\auto.dta"
(1978 automobile data)

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        make |          0
       price |         74    6165.257    2949.496       3291      15906
         mpg |         74     21.2973    5.785503         12         41
       rep78 |         69    3.405797    .9899323          1          5
    headroom |         74    2.993243    .8459948        1.5          5
-------------+---------------------------------------------------------
       trunk |         74    13.75676    4.277404          5         23
      weight |         74    3019.459    777.1936       1760       4840
      length |         74    187.9324    22.26634        142        233
        turn |         74    39.64865    4.399354         31         51
displacement |         74    197.2973    91.83722         79        425
-------------+---------------------------------------------------------
  gear_ratio |         74    3.014865    .4562871       2.19       3.89
     foreign |         74    .2972973    .4601885          0          1

. codebook rep78

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
rep78                                                                                                                                                        Repair record 1978
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (int)

                 Range: [1,5]                         Units: 1
         Unique values: 5                         Missing .: 5/74

            Tabulation: Freq.  Value
                            2  1
                            8  2
                           30  3
                           18  4
                           11  5
                            5  .

.