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| = Survey Sampling = <<TableOfContents>> ---- == 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. ---- CategoryRicottone |
