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Let's say I have a population stratified by gender and age group. Having their proportions, how should I choose the sampling units for interview? How do I ensure the defined quotas are met?

If the interviewer, for example, have already achieved quotas for males, should it refrain to interview a 85+ years old male, so he can achieve its age group quota (a rare one)?

What if he can't determine the caractheristics beforehand? Should he eliminate the observation?

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If your population is stratified in two dimensions, eg gender and age group, you should define a separate quota for each possible combination of the two dimensions, as illustrated in this example. Then provided none of the quotas are exceeded, you can never get into the position of having achieved the overall quota for males, but not achieved the quota for males of a particular age-group.

If a characteristic cannot be determined in advance, eg age-group when interviewing strangers in the street, this may sometimes result in a quota being exceeded. It would then be appropriate to eliminate the observation, to ensure that the sample exactly satisfied the pre-determined quotas. Assuming that the quotas are representative of the population, inclusion of additional observations could result in over-representation of some combinations of characteristics, in other words a biased sample, which could easily lead to biased conclusions.

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  • $\begingroup$ What if quotas can't be met? It's also appropriate to eliminate observations to ensure population proportions? If affirmative, how should one proceed with that? Removing random or last observations? $\endgroup$ – celiomsj Jul 31 '14 at 19:47
  • $\begingroup$ @celiomsj You might like to raise these points as a new question. Then they are likely to be seen by more participants, and there is more space for answers than comments permit. $\endgroup$ – Adam Bailey Jul 31 '14 at 20:54

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