Respondent-Driven Sampling and Total Population Data from a Rural Ugandan Cohort, 2010: Special Licence Access

DOI

Abstract copyright UK Data Service and data collection copyright owner.

This is a mixed-methods data collection. This study used Respondent Driven Sampling (RDS) methodology, which is a sampling method designed to generate unbiased estimates of population characteristics for populations where a sampling frame is not available. It is a form of snowball or link-tracing sampling, where respondents are given coupons to recruit other members of the target population, and where respondents are rewarded for both participating and for recruiting others. In addition to variables of interest, data are collected on the number of members of the target population each participant knows. Estimation methods are then applied to account for the non-random sample selection in an attempt to generate unbiased estimates for the target population. In 2010, the researchers conducted an RDS study in a rural Ugandan population where total population data were available. The aim of this study was to evaluate whether RDS could generate representative data on a rural Ugandan population by comparing estimates from an RDS survey with total-population data. The data used to define the target population (male household heads) were available from an ongoing general population cohort of 25 villages in rural Masaka, Uganda covering an area of approximately 38km. Annually, households in the study villages are mapped and after obtaining consent, a total-population household census and an individual questionnaire are administered and blood taken for HIV-1 testing. A random sample of eligible men in the target population who were not recruited during the RDS study were also interviewed, using the same RDS questionnaire. Finally, 49 qualitative interviews (of which summaries have been deposited) were conducted with a range of people (men and women) including RDS participants and non-participants, and RDS interviewers. These data can be used to evaluate the RDS sampling method, and to test new RDS estimators. Further information may be found in the documentation and in the journal articles listed in the Publications section. Special Licence access and geographic data This data collection is subject to Special Licence access conditions (see Access section for details). Data are analysable at individual village level, and GPS point data are available for the villages and interview sites. Finer detail geographic variables may be available for certain research questions. If these are required, users should request this when making their Special Licence application.

Main Topics:

Quantitative data: demographic characteristics of the individual, including household composition, age, HIV status, tribe, religion, relationship between target population sample member and contacts, geographic data. Qualitative interview summaries: respondents' opinions of the study, the conduct of the research and the incentives used.

Respondent Driven Sampling methods were used - see Abstract and documentation for details.

Face-to-face interview

Identifier
DOI http://doi.org/10.5255/UKDA-SN-7462-1
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=950eec258bbaabae2c1ed5de6b56ea9d792d225adb431209814090d22d36a234
Provenance
Creator Medical Research Council, Uganda Virus Research Institute (MRC/UVRI); White, R., London School of Hygiene & Tropical Medicine
Publisher UK Data Service
Publication Year 2014
Funding Reference Medical Research Council
Rights Copyright R. White and P. Kaceebu (Director of Uganda Virus Research Institute (MRC/UVRI)); <p>The Data Collection is available to UK Data Service registered users subject to the <a href="https://ukdataservice.ac.uk/app/uploads/cd137-enduserlicence.pdf" target="_blank">End User Licence Agreement</a>.</p><p>Commercial use is not permitted.</p><p>Use of the data requires approval from the data owner or their nominee. Users must apply for access via a Special Licence application.</p>
OpenAccess true
Representation
Language English
Resource Type Text; Numeric
Discipline Social Sciences
Spatial Coverage Uganda