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Survey sampling issues in primary care research.

Arch G. Mainous, James G. Hougland

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Abstract

Survey research methods are often used to answer questions in primary care medicine. Consequently, investigators must understand and address sampling issues. Probability sampling designs have particular utility for questions that seem most appropriate for survey research. These designs provide each member of the population with a known probability of selection, and if performed properly with an appropriate sample size, they provide a sample with essentially no selection bias. Examples of random and stratified sampling designs are presented. These two probability designs, along with nonprobability sampling techniques (convenience, purposive, quota), are discussed in terms of bias, error, and possible limitations.

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What this paper is about

Survey research methods are often used to answer questions in primary care medicine. Consequently, investigators must understand and address sampling issues. Probability sampling designs have particular utility for questions that seem most appropriate for survey research. These designs provide each member of the population with a known probability of selection, and if performed properly with an appropriate sample size, they provide a sample with essentially no selection bias. Examples of random and stratified sampling designs are presented. These two probability designs, along with nonprobability sampling techniques (convenience, purposive, quota), are discussed in terms of bias, error, and possible limitations.

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Available abstract

Survey research methods are often used to answer questions in primary care medicine. Consequently, investigators must understand and address sampling issues. Probability sampling designs have particular utility for questions that seem most appropriate for survey research. These designs provide each member of the population with a known probability of selection, and if performed properly with an appropriate sample size, they provide a sample with essentially no selection bias. Examples of random and stratified sampling designs are presented. These two probability designs, along with nonprobability sampling techniques (convenience, purposive, quota), are discussed in terms of bias, error, and possible limitations.

Key concepts: Nonprobability sampling, Probability sampling, Sampling design, Stratified sampling, Sampling (signal processing), Survey sampling, Selection (genetic algorithm), Sample (material)

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