I have used mutli-stage sampling (i.e. cluster and stratified sampling) to select four units within a geographical area. Each unit was selected randomly from a list of that unit. There are only four different types of units in the geographical area, so the unit selected is representative of each unit type. (I established some minimum criteria to ensure the chosen unit is representative of all units of the same type e.g. in terms of size. e.g. the chosen unit must have about 100 people because the the size of all units of a particular type is ranges from 50 to 150 people, so this is sort of an average.)
Note: The geographical area meets basic criteria I have established e.g. it must include all unit types present in the overall area. The geographical area is part of the overall area e.g. a village in one part of a country).
I have then randomly selected people belonging to each unit (e.g. 100 people from unit 1, 100 people from unit 2, 100 people from unit 3, and 100 people from unit 4).
My sample size is then 400 people (belonging to four representative units within the geographical area). I consider this to be a representative sample based on a stratification of unit type.
My problem is that I am unsure how representative the total members of each unit are in regard to the population of the geographical area. i.e, there may be more men in unit 1 but less men in the geographical area. Or, more older people in unit 2, compared to the geographical area.
In this case, is it necessary for the 400 people in my sample to resemble the demographic breakdown of the geographical area. I am unsure how this is possible but feel that it is not possible, as my sample of 400 people is representative of the unit type, not the geographical area.
Note: By "representative", I mean that the sample broadly reflects the population characteristics e.g. if there are 100 males and 90 females in the population, this ratio would be broadly reflected in the sample.