This article presents a discussion of mixed methods (MM) sampling techniques. MM sampling involves combining well-established qualitative and quantitative techniques in creative ways to answer research questions posed by MM research designs. Several issues germane to MM sampling are presented including the differences between probability and purposive sampling and the probability-mixed-purposive sampling continuum. Four MM sampling prototypes are introduced: basic MM sampling strategies, sequential MM sampling, concurrent MM sampling, and multilevel MM sampling. Examples of each of these techniques are given as illustrations of how researchers actually generate MM samples. Finally, eight guidelines for MM sampling are presented.

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Mixed Methods Sampling A Typology With Examples

During the past two decades we have witnessed a rather impressive growth of theoretical innovations and conceptual revisions of epistemological and methodological approaches within constructivist‐qualitative quarters of the social sciences. Methodological discussions have commonly addressed a variety of methods for collecting and analyzing empirical material, yet the critical grounds upon which these were reformulated have rarely been extended to embrace sampling concepts and procedures. The latter have been overlooked, qualifying only as a ‘technical’ research stage. This article attends to snowball sampling via constructivist and feminist hermeneutics, suggesting that when viewed critically, this popular sampling method can generate a unique type of social knowledge—knowledge which is emergent, political and interactional. The article reflects upon researches about backpacker tourists and marginalized men, where snowball sampling was successfully employed in investigating these groups' organic social ne...

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Sampling Knowledge: The Hermeneutics of Snowball Sampling in Qualitative Research

This paper provides a framework for developing sampling designs in mixed methods research. First, we present sampling schemes that have been associated with quantitative and qualitative research. Second, we discuss sample size considerations and provide sample size recommendations for each of the major research designs for quantitative and qualitative approaches. Third, we provide a sampling design typology and we demonstrate how sampling designs can be classified according to time orientation of the components and relationship of the qualitative and quantitative sample. Fourth, we present four major crises to mixed methods research and indicate how each crisis may be used to guide sampling design considerations. Finally, we emphasize how sampling design impacts the extent to which researchers can generalize their findings. Key Words: Sampling Schemes, Qualitative Research, Generalization, Parallel Sampling Designs, Pairwise Sampling Designs, Subgroup Sampling Designs, Nested Sampling Designs, and Multilevel Sampling Designs

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A Typology of Mixed Methods Sampling Designs in Social Science Research

Despite the abundance of published material on conducting focus groups, scant specific information exists on how to analyze focus group data in social science research. Thus, the authors provide a ...

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A Qualitative Framework for Collecting and Analyzing Data in Focus Group Research

Come take a walk with me: the "go-along" interview as a novel method for studying the implications of place for health and well-being.

Approaches to sampling and case selection in qualitative research: examples in the geography of health.

Developing socio-spatial knowledge networks: a qualitative methodology for chronic disease prevention.

This article introduces a new theory of geographical analysis, sociospatial knowledge networks, for examining and understanding the spatial aspects of health knowledge (i.e., exactly where health beliefs and knowledge coincide with other support in the community). We present an overview of the theory of sociospatial knowledge networks and an example of how it is being used to guide an ongoing ethnographic study of health beliefs, knowledge, and knowledge networks in a rural community of African Americans, Latinos, and European Americans at high risk for, but not diagnosed with, type 2 diabetes mellitus. We believe that the geographical approach to understanding health beliefs and knowledge and how people acquire health information presented here is one that could serve other communities and community health practitioners working to improve chronic disease outcomes in diverse local environments.

Sarah A. Washburn

Papers

Approaches to sampling and case selection in qualitative research: examples in the geography of health.

Developing socio-spatial knowledge networks: a qualitative methodology for chronic disease prevention.

Sociospatial knowledge networks: Appraising community as place