Respondent-Driven Sampling: A Rigorous and Practical Sampling Method for Nursing Research

2.50
Hdl Handle:
http://hdl.handle.net/10755/156440
Type:
Presentation
Title:
Respondent-Driven Sampling: A Rigorous and Practical Sampling Method for Nursing Research
Abstract:
Respondent-Driven Sampling: A Rigorous and Practical Sampling Method for Nursing Research
Conference Sponsor:Sigma Theta Tau International
Conference Year:2006
Author:Jarrin, Olga, RN, BSN
P.I. Institution Name:University of Connecticut
Title:Doctoral Student
Respondent-driven sampling (RDS) is a relatively new probability sampling method developed by Heckathorn, which has the potential to revolutionize nursing research. An initial set up subjects or ?seeds? selected by the researcher are invited to recruit additional participants through their personal networks. This process is repeated and after 3-5 waves the sample will begin to have the characteristics and properties of a sample drawn at random from the target population. At first glance RDS appears similar to chain-referral or snowball sampling, however the difference lies in the recruitment process, which reduces bias through primary and secondary incentives and allows the calculation of selection probabilities. External validity is high as recruitment is not limited to subgroup members who are accessible to the researcher, but rather extends the sample to all potential members of a subgroup by accessing respondents through their social networks. Additional features of RDS include utility for estimation of hidden population size, the study of social structure, and the study of social inequality. This development in sampling methodology has implications for the design of future research studies, including meta-analyses, and also has implications for consumers of research who are attempting to determine if the results of a study can be generalized to their population of interest. Examples from previous and planned research are used to illustrate the benefits and challenges of respondent driven sampling for nursing research.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleRespondent-Driven Sampling: A Rigorous and Practical Sampling Method for Nursing Researchen_GB
dc.identifier.urihttp://hdl.handle.net/10755/156440-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Respondent-Driven Sampling: A Rigorous and Practical Sampling Method for Nursing Research</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2006</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Jarrin, Olga, RN, BSN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Connecticut</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Doctoral Student</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">olga.jarrin@uconn.edu</td></tr><tr><td colspan="2" class="item-abstract">Respondent-driven sampling (RDS) is a relatively new probability sampling method developed by Heckathorn, which has the potential to revolutionize nursing research. An initial set up subjects or ?seeds? selected by the researcher are invited to recruit additional participants through their personal networks. This process is repeated and after 3-5 waves the sample will begin to have the characteristics and properties of a sample drawn at random from the target population. At first glance RDS appears similar to chain-referral or snowball sampling, however the difference lies in the recruitment process, which reduces bias through primary and secondary incentives and allows the calculation of selection probabilities. External validity is high as recruitment is not limited to subgroup members who are accessible to the researcher, but rather extends the sample to all potential members of a subgroup by accessing respondents through their social networks. Additional features of RDS include utility for estimation of hidden population size, the study of social structure, and the study of social inequality. This development in sampling methodology has implications for the design of future research studies, including meta-analyses, and also has implications for consumers of research who are attempting to determine if the results of a study can be generalized to their population of interest. Examples from previous and planned research are used to illustrate the benefits and challenges of respondent driven sampling for nursing research.</td></tr></table>en_GB
dc.date.available2011-10-26T14:47:07Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T14:47:07Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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