Quota sampling is a type of non-probability sampling method in which the researcher intentionally selects participants based on specific characteristics or traits to ensure that the sample represents certain subgroups in proportion to their presence in the population.
Unlike probability sampling methods, where individuals are randomly selected, quota sampling involves setting predefined quotas for specific characteristics and selecting individuals who meet those criteria until the quotas are filled.
Some advantages of quota sampling are:
- Cost-effective: Quota sampling can be more cost-effective than some probability sampling methods, especially when obtaining a complete list of the population is challenging.
- Efficiency: It allows researchers to efficiently achieve a sample that reflects specific characteristics without random selection.
- Control over sample composition: Researchers have greater control over the sample’s composition, ensuring that specific subgroups are adequately represented.
Some disadvantages of quota sampling are:
- Risk of bias: Quota sampling may introduce bias if the selection process is not carefully managed. The researcher’s judgment in selecting participants can influence the sample composition.
- Limited generalizability: Findings from quota samples may have limited generalizability to the broader population, especially if the quotas do not accurately reflect the population’s diversity.
- Subjectivity: The subjectivity in selecting participants may lead to unintentional biases based on the researcher’s assumptions or judgments.
- Not suitable for all populations: Quota sampling may not be suitable for populations where characteristics are not easily identifiable or when the desired quotas are challenging to define.
List of recommended resources #
For a broad overview #
This blog on QuestionPro gives an overview of quota sampling, its pros and cons and characteristics. The blog illustrates the concept with examples for better understanding of the reader as well as provides steps to perform quota sampling.
This blog entry on Scribbr by Kassiani Nikolopoulou gives a brief overview of quota sampling, a non-probability sampling technique that relies on the non-random selection of a predetermined number or proportion of units. The blog gives a step-by-step guide to quota sampling as well as details the different types of quota sampling methods.
For in depth understanding #
This article by Arkadiusz Wiśniowski, Joseph W Sakshaug, Diego Andres Perez Ruiz and Annelies G Blom evaluates supplementing inferences based on small probability samples with prior distributions derived from non-probability data. It further demonstrates that informative priors based on non-probability data can lead to reductions in variances and mean squared errors for linear model coefficients.
This book explores the increasingly scientific endeavor of surveys and their growing complexity, as different information sources and data collection modes are combined. Chapter 22 of this book, written by Vasja Vehovar, Vera Toepoel & Stephanie Steinmetz, deals particularly with non-probability sampling.
Case study #
This paper by Thomas Gschwend studies the case of analyzing French data as there is no random sampling in France. The essay suggests some strategies for successfully dealing with such enquiries during the peer-review process and presents quota sampling as one such strategy.
This paper by Inas Nurfadia Futri, Tastaftiyan Risfandy, and Mansor H. Ibrahimb describes an alternative method, i.e. quota sampling, for obtaining a representative sample of households using an internet-based survey at an affordable cost without ignoring the validity of the survey.