Sampling 06: Non-Probability Sampling

Non-Probability Sampling Overview

  • Definition: A method of sampling that does not involve any random selection.

  • Key Point: Lacks randomness, which can lead to sampling bias.

Types of Non-Probability Sampling

Convenience Sampling

  • Also known as: Accidental sampling or haphazard sampling.

  • Definition: Sampling based on what is most convenient for the researcher.

  • Example:

    • Studying smokers who visit the emergency room between 4:00 p.m. and 7:00 p.m.

    • Limitation: May only capture employed smokers, missing data about unemployed smokers or those who visit at other times, leading to confounding factors.

Snowball Sampling

  • Definition: Participants are recruited through referrals from other participants.

  • Process: One participant refers friends who then refer more friends, creating a chain of referrals.

  • Limitation: Participants may share common social characteristics, leading to confounding variables.

Purposive Sampling

  • Also known as: Judgmental sampling.

  • Definition: The researcher exercises judgment to select participants.

  • Method: Researchers decide who is included based on their own criteria.

  • Limitation: Non-random selection can introduce bias based on the researcher’s perceptions of importance, leading to potential confounding variables.

Voluntary Sampling

  • Definition: Participants self-select to be included in the study.

  • Characteristic: Often individuals who feel strongly about an issue or have personal reasons to participate.

  • Limitation: The self-selection process can introduce bias, as participants may not represent the broader population.

Common Themes in Non-Probability Sampling

  • Lack of Randomness: All these methods involve non-random selection, which is key to generating bias.

  • Confounding Variables: Reduced ability to control for confounding factors that may influence results.

  • Potential for Bias: Non-probability sampling techniques are more likely to produce biases compared to probability sampling methods, which aim for random selection.

Conclusion

  • Understanding the limitations of non-probability sampling is crucial in research to avoid skewed results.

  • While probability sampling is essential for minimizing bias, researchers must be cautious when using non-probability methods to ensure the validity of their findings.