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Methods of survey sampling
Nonprobability Sampling
Describe it
Methods include? Issues with these methods?
A collection of methods that do not rely on formal random techniques to identify the units to be included
Methods include..
Judgment sampling
Representive units of pop. selected by the investigator
Convenience sampling
Sample selected because its easy to obtain
convenience or judgment sampling often produces
biased results
Purposive sampling
Select units based on known exposure or disease status
Purposive sampling is often used to select units for analytic observational studies (e.g. case-control), but it is inadequate for obtaining data to estimate population parameters
Simple Random Sampling
Definition?
One selects a fixed percentage of the population using a formal random process; as for example, flipping a coin or die, drawing numbers from a hat, using random number generators or random number tables
Systematic Random Sampling
Definition?
Benefits?
COns?
Sampling the n sampling units are selected from the sampling frame at regular intervals (e.g., every fifth farm or every third animal
Pros
Practical way to obtain a representative sample
Sample distributed evenly across entire pop.
Cons
Characteristic being observed could be related to interval itself
Difficulty of quantitatively assessing the variability of estimates obtained by systematic random sampling
Stratified Random Sampling
Definition?
In stratified sampling, prior to selection, the sampling frame is divided into strata based on factors likely to influence the level of the characteristic (e.g. prevalence of antibodies) being estimated.
Then a simple random or systematic random sample is selected within each stratum
Stratified sampling is more flexible than simple random sampling because?
Another benefit?
Different sampling percentage can be used in the various strata (e.g. 2% in one stratum and 5% in another)
Sample estimate precision improved as only the within-stratum variation contributes to the variation (standard error) of the mean in stratified sampling
Cluster Sampling
Definition?
Describe the clusters
initial sampling unit is larger than the unit of concern (e.g. usually the individual).
Clusters of individuals often arise naturally (e.g. litters, pens, or herds) or they may be formed artificially (e.g. geographic clusters)
Clusters (sampling units) can be selected by systematic, simple, or stratified random methods; all individuals within the sampling units are tested.
Multistage Sampling
Describe it
How is it implemented?
similar to cluster sampling except that sampling takes place at all stages
Example - two stage sampling
First stage: selecting a sample of
the primary units (e.g. herds) listed in the sampling frame THEN within each unit a sample of 2NDARY units would be selected
Multistage sampling is used because of its practical advantages and flexibility
Why?
The number of primary (n1) and secondary units (n2) may be varied to account for different costs of sampling primary versus secondary units as well as the variability of the characteristic being estimated
Multistage Sampling
Whenever possible, one should select each stage's sampling units with?
Why?
probability proportional to the number of individuals they contain
minimizes the error of estimate and stabilizes the sample size
The main disadvantage of cluster and multistage samples is that?
more individuals may be required in the sample to obtain the same precision as would be expected if individuals could be selected with simple random sampling
Sample size for determining the prevalence
Calculating the confidence interval for a positive survey result