Survey Sampling

Sample Frames

Common frames used for survey sampling are:

• Census Bureau surveys are excellent sources of regional, hierarchical data (i.e. states > counties > tracts)

• U.S. Postal Service Delivery Sequence files
• Random digit dialing (RDD)

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.

• Equal allocation is taking the same number from each stratum.

• Proportional allocation is taking a number proportional to the size of that stratum.

• Neyman allocation is an optimization of a key measure's margin of error against cost. It assumes a fixed cost per contact.

• On the other hand, if cost is assumed variable, it becomes an optimal allocation.

Note that, if all measures are equally varied, proportional allocation is essentially the same as a Neyman allocation.

Sampling Methods

Simple Random Sampling (SRS) is essentially sorting randomly and taking the first N cases.

Stratified Random Sampling (STSRS) is the above process applied to a stratified sample, using proportional allocation.

Systematic sampling is any form of sampling that takes every Nth case from a list. The key is then how the list is ordered.

Probability Proportionate to Size (PPS) ensures that chance to be contacted increases with the magnitude of some measure. For example, in a study of utility customers, the largest consumers of that utility should almost always be contacted.

Multi-Stage Methods

Randomly select primary sampling units (PSU) like census tracts, then randomly select the actual targets (i.e. households) as secondary sampling units (SSU).

Cluster sampling is a two-stage method where all members of the sampled PSUs are contacted.

Common in face-to-face interviews, due to extraordinary costs of that mode.

Multi-Phase Methods

Sample for a screener, then re-sample based on the information collected in the screener. In most cases, all responses from the target group are re-contacted, while a random sample of others are re-contacted.

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