What is grounded theory and how does theoretical sampling function within it?

What is grounded theory and how does theoretical sampling function within it?

• A. Grounded theory tests existing theories using hypothesis testing.
• B. Grounded theory aims to develop theory from data; theoretical sampling selects new cases to elaborate emerging concepts until theoretical saturation is reached.
• C. Theoretical sampling selects cases randomly to generalize.
• D. Grounded theory means analyzing data in a vacuum without sampling changes.

Answer: (B)

Grounded theory is a research approach that aims to generate theory directly from data rather than test pre-existing hypotheses. It involves collecting and analyzing data in tandem, using iterative coding and constant comparison to identify concepts, relate them into categories, and build an explanatory framework grounded in the data itself. Theoretical sampling is a key mechanism in this approach. As and when preliminary concepts emerge, researchers purposefully select new cases, sources, or contexts that can illuminate, refine, or challenge those ideas. This isn’t about random generalization; it’s about choosing what will most inform the developing theory. The process continues until theoretical saturation is reached, meaning additional data no longer bring new properties or dimensions to the emerging categories. Other approaches that emphasize testing existing theories, random sampling for generalization, or analyzing data without adapting data collection do not fit grounded theory. Grounded theory focuses on theory construction from data through purposeful convergence of sampling and analysis, not on hypothesis testing, random generalization, or static analysis without sampling adjustments.

Grounded theory is a research approach that aims to generate theory directly from data rather than test pre-existing hypotheses. It involves collecting and analyzing data in tandem, using iterative coding and constant comparison to identify concepts, relate them into categories, and build an explanatory framework grounded in the data itself.

Theoretical sampling is a key mechanism in this approach. As and when preliminary concepts emerge, researchers purposefully select new cases, sources, or contexts that can illuminate, refine, or challenge those ideas. This isn’t about random generalization; it’s about choosing what will most inform the developing theory. The process continues until theoretical saturation is reached, meaning additional data no longer bring new properties or dimensions to the emerging categories.

Other approaches that emphasize testing existing theories, random sampling for generalization, or analyzing data without adapting data collection do not fit grounded theory. Grounded theory focuses on theory construction from data through purposeful convergence of sampling and analysis, not on hypothesis testing, random generalization, or static analysis without sampling adjustments.