Survey Sampling
Contents
Sample Type
Propability sampling
All members of a population have a non-zero chance to be contacted in a survey instrument. Traditional statistics rely on this assumption.
Examples:
- Administrative surveys
- Surveys with random recruitment (as by random digit dialing)
Non-probability sampling
Some members of a population are certain to be contacted or not be contacted.
Examples:
- Panel surveys
- River surveys (i.e. surveys with open recruitment, as by banner ads)
Survey Allocation
Allocation is the distribution of sample size across domains.
Designing Domains
The key considerations are:
- are some splits more important to others?
- if studying military recruitment, then sex/gender is a strong split
- what splits will be used for reporting? + what is the expected response rate?
- if too few responses are expected from a domain, then splits should be reconsidered
- what is the desired margin of error?
Stratified Allocation
Stratification is the process of dividing the population into discrete stratum, and then sampling from the strata.
Within a stratified sample, allocation can be designed as:
- equal from each stratum
- proportional to the size of each stratum
- an optimization of a key measure's margin of error against cost
- if cost is assumed fixed per unit, it is a Neyman allocation
- if cost is assumed variable, it is an optimal allocation
- note that, if all measures are equally varied, proportional allocation is essentially the same as a Neyman allocation