Convenience sampling is a non-probability sampling method where individuals or elements are selected based on their accessibility and convenience to the researcher. In this approach, the sample is drawn from individuals who are readily available or easily accessible rather than through a random or systematic method. Convenience sampling is often used when time, cost, or other practical considerations limit the researcher’s ability to obtain a more representative sample.
Some key features of convenience sampling are:
- Accessibility: Participants are chosen based on their availability and proximity to the researcher.
- Non-random selection: Convenience sampling does not involve random selection or systematic methods. Instead, participants are selected based on convenience.
- Informal process: The selection process is often informal, and participants may be those who are most easily accessible or willing to participate.
Advantages of convenience sampling include:
- Ease of implementation: Convenience sampling is easy and quick to implement, making it suitable for exploratory research or situations with time constraints.
- Cost-effective: It can be cost-effective, especially when obtaining a comprehensive list of the entire population is impractical or expensive.
- Useful for pilot studies: Convenience sampling is often used in pilot studies or preliminary investigations to gather initial insights before committing to a more extensive sampling method.
Some disadvantages of convenience sampling include:
- Sampling bias: Convenience sampling may introduce bias into the sample, as participants are not selected randomly or systematically. The sample might not be representative of the entire population.
- Limited generalizability: Findings from convenience samples may have limited generalizability to the wider population, as certain groups may be overrepresented or underrepresented.
- Lack of control: The researcher has limited control over the sample’s composition, and certain demographic or characteristic groups may be underrepresented.
- Risk of self-selection bias: Participants who volunteer or are easily accessible may have characteristics that differ systematically from those omitted, leading to self-selection bias.
List of recommended resources #
For a broad overview #
Population Research: Convenience Sampling Strategies
This paper by Samuel J. Stratton gives a brief overview of convenience sampling strategies generally used for population and clinical research. It also provides various methods for improving dependability of convenience sampling.
What Is Convenience Sampling? | Definition & Examples
This article by Kassiani Nikolopoulou on Scribbr gives an overview of convenience sampling, a type of non-probability sampling. The article discusses various convenience sampling examples, how to reduce bias in convenience sampling as well as the advantages and disadvantages of convenience sampling.
For in depth understanding #
Convenience sampling method: How and when to use it?
This blog by Qualtrics XM is an ultimate guide to understanding convenience sampling, one of the most common non-probability sampling methods. It discusses how convenience sampling works, why it is important for businesses along with examples illustrating the same, how to use convenience sampling without skewing data collection and how to analyze convenience sampling data.
The Inconvenient Truth About Convenience and Purposive Samples
This article by Chittaranjan Andrade thoroughly explains the concepts involved in convenience sampling with the help of examples of both good and bad sampling practices.
Case study #
A multi-group analysis of convenience samples: free, cheap, friendly, and fancy sources
This article by Bradley G. Winton and Misty A. Sabol compares the impact of sample source type based on composite-based theoretical model relationships. The study tests four different sample sources empirically to assess differences in construct measurement and structural models to determine how sample source can impact empirical results.
Comparing convenience and probability sampling for urban ecology applications
This research article by Andrew Speak, Francisco J. Escobedo, Alessio Russo, and Stefan Zerbe uses two spatially extensive convenience samples of the urban forest of Meran (Italy), and compares the tree characteristics, community structure, and ecosystem service provision with 200 random circular plots.
References #
Convenience Sampling: Definition, Advantages, and Examples
