sampling strategies

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Posted by: | Posted on: October 27, 2008

“Sampling Strategies”

Kandace J. Landreneau, RN, PhD, CCTC, Post-Doctoral Research Fellow, University of California-San Francisco, Walnut Creek, CA, Research Committee Member

What is a sample?
A sample is a subset of your population by which you select to be participants in your study.

What is sampling?
Sampling is simply stated as selecting a portion of the population, in your research area, which will be a representation of the whole population.

What are sampling strategies?
The strategy is the plan you set forth to be sure that the sample you use in your research study represents the population from which you drew your sample. For example, if your study included the living donors then the strategy you chose to enter them would help support that they are representative of all living donors.

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Posted by: | Posted on: September 20, 2008

Sampling Strategies

Key Points:

  • Probability sampling is a mechanism for reducing bias in the selection of samples.
  • Ensure you become familiar with key technical terms in the literature on sampling such as: representative sample; random sample; non-response; population; sampling error; etc.
  • Randomly selected samples are important because they permit generalizations to the population and because they have certain known qualities.
  • Sampling error decreases as sample size increases.
  • Quota samples can provide reasonable alternatives to random samples; but they suffer from some deficiencies.
  • Convenience samples may provide interesting data, but it is crucial to be aware of their limitations in terms of generalizability.
  • Sampling and sampling-related error are just two sources of error in social survey research.

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