Choosing the Right Non-Probability Sampling Design in Research

Abstract

Background: Sampling, a process of selecting a representative subset of a population, is an essential phase in research. A sampling design is a structured plan for obtaining a sample, and non-probability sampling designs are commonly used in qualitative research. Selecting an appropriate sampling design is crucial for conducting methodologically sound research, yet researchers frequently lack clear guidance on choosing the most suitable design for a given study context.

Objective: This study examines various non-probability sampling designs and provides guidelines for selecting the most appropriate design based on research context and purpose. Methods:  Through a systematic review of literature from secondary sources, the study analyzed secondary data / texts from books, journal articles, and online sources published between 2021 and 2025.

Findings: The findings indicate that no single non-probability sampling design is suitable for all research studies and offer researchers clear guidance on the types of non-probability sampling designs and their appropriate applications.

Conclusion: The study highlights that no single non-probability sampling design can universally fit all research contexts. Instead, the choice of design should be guided by the specific objectives, nature of the study, and available resources. The findings provide researchers with practical guidance on the strengths, limitations, and appropriate applications of different non-probability sampling methods, enabling more informed decisions that enhance the validity and relevance of their research outcomes.

Novelty: The novelty of this research is its practical guidance, showing that non-probability sampling designs should be chosen based on study objectives and context to improve validity and relevance.