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Gaining Access to Economically Marginalized Rural Populations: Lessons Learned from Nonprobability Sampling

Authors


  • This research was supported in part by USDA/CSREES/NRICGP Grant No. 2001-35401-10215 and 2002-35401-11591, 2004-35401-14938. Data were collected in conjunction with the cooperative multistate research project, NC-223/NC-1011, “Rural Low–Income Families: Monitoring Their Well-being and Functioning in the Context of Welfare Reform.” Cooperating states are California, Indiana, Iowa, Kentucky, Louisiana, Massachusetts, Maryland, Michigan, Minnesota, Nebraska, New Hampshire, New York, Ohio, Oregon, and South Dakota. We gratefully acknowledge the assistance of Ethan Robert Young, undergraduate research assistant at the University of Massachusetts Amherst.

Abstract

Poverty is a significant problem in rural America. Gaining access to economically marginalized rural populations in order to recruit individuals to participate in a research study, however, is often a challenge. This article compares three different nonprobability sampling techniques that have been used to recruit rural, low-income mothers—purposive sampling, respondent-driven sampling, and mixed purposive sampling. We review the relative advantages and drawbacks of the three methods in terms of access to the targeted population, methods of recruitment, size of the sample pool, randomness of the sample, generalizability of results, and researchers' control over the process.

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