TV4001 - Epidemiology 6 - Survey sampling

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24 Terms

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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

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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

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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

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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

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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

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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.

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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

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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

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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

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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

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Sample size for determining the prevalence

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Calculating the confidence interval for a positive survey result

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