Hello everybody, have a lovely weekend.
I have a question.
I have a data set from the survey of living condition for Bolivians household 38201 persons to 15 to >60 years old.
My intentions make a probit model for the probability of been consumer (been smokers) And there are 26694 smokers whit depending variable 1= smoke 0= No smoke, and independent variables, age, wage, educations degree, gender, consume alcohol, etc. All of these are categorical variables, ones of them dummy another's categoricals.
However, when I ran the probit regression, my result the Number of obs are 26694. So far, so good. Wen adds a condition to this regression like "if extreme_poor==1" (extreme poor is a dummy variable where 1 is a person has a low income 5739 obs and 0= otherwise and has 32440 obs ) the result of regression show only 3389 obs.

My tutors give a bit of advice, construct the dependent variable whit 3 categorizations 1= consume tobacco 2= no consume tobacco a 3= never consume tobacco, this lates category must be capturing all person never answered the inquire for smoke or no smoke plus missing plus another.

This advice neither helped.

In my data set for the independent's variables, I found some have a few responses, or the main category has few 1's many 0's. I meant, Some variables I use as an independent variable the'ar shorter than the dependent variable.

Sorry for writing a lot but I try to put the context I want to ask you.

¿How you tell this in the par of description of data set in a paper for a journal?

Thank you in advance.