Bias decomposition and estimator performance in respondent-driven sampling

Respondent-Driven Sampling (RDS) is a method of network sampling that is used to sample hard-to-reach populations. The resultant sample is non-random, but different weighting methods can account for the over-sampling of (1) high-degree individuals and (2) homophilous groups that recruit members more effectively. While accounting for degree-bias is almost universally agreed upon, accounting for recruitment-bias has been debated as it can further increase estimate variance without substantially reducing bias. Simulation-based research has examined which weighting procedures perform best given underlying population network structures, group recruitment differences, and sampling processes. Yet, in the field, analysts do not have a priori knowledge of the network they are sampling. We show that the RDS sample data itself can determine whether a degree-based estimator is sufficient. Formulas derived from the decomposition of a ‘dual-component’ estimator can approximate the ‘recruitment component’ (RC) and ‘degree component’ (DC) of a sample’s bias. Simulations show that RC and DC values can predict the performance of different classes of estimators. Samples with extreme ‘RC’ values, a consequence of network homophily and differential recruitment, are better served by a classical estimator. The use of sample data to improve estimator selection is a promising innovation for RDS, as the population network features that should guide estimator selection are typically unknown.     

Strategies for Measuring and Promoting Mothers' Social Support Networks

ABSTRACT

This chapter recommends respondent-driven sampling (RDS) and peer-driven intervention (PDI) as new strategies for improving safe motherhood and women's health in countries where women have limited access to information and communication technology. Strategies for measuring and promoting mothers' social support networks could be applied to enrich communication about reproductive health and safe motherhood, especially in countries where women's low social status leads to child marriage, low educational attainment/illiteracy, and limited access to modern information and communication technology. By using RDS to study communities and social network structures, outreach workers can educate women via women's social support groups, enhancing and broadening the use of modern information and communication technologies. RDS is a strategy that allows researchers to identify and focus on distinct groups within a community. PDI uses a two-step intervention where respondents are educated by outreach workers and previous participants (members of social support groups). Limitations of these approaches are also discussed.     

Comparing the effectiveness of respondent-driven sampling and quota sampling in migration research

We evaluate the effectiveness in empirical migration research of the respondent-driven sampling (RDS) and the quota sampling with regard to four criteria: quality of the data; sociometric diversity of the sample; geographic coverage of the sample; and cost-effectiveness. We review two surveys of ex-USSR migrants, conducted simultaneously in the Warsaw metropolitan area, each undertaken with the use of one of the two sampling methods. We find that although the RDS was considerably costlier, it enabled faster data collection and posed a lower risk of underestimating the cost of the survey. We also find that the RDS generated higher-quality data, and that it was more successful in surveying short-term circular migrants. This comparative evaluation contributes to the literature on social research methods in that it links the sampling methods with the quality and character of the data, and helps assess the usefulness and applicability of RDS in empirical migration studies.     

Social network analysis with respondent-driven sampling data: A study of racial integration on campus

This paper presents respondent-driven sampling (RDS) as a viable method of sampling and analyzing social networks with survey data. RDS is a network based sampling and analysis method that provides a middle ground compliment to ego-centric and saturated methods of social network analysis. The method provides survey data, similar to ego-centric approaches, on individuals who are connected by behaviorally documented ties, allowing for macro-level analysis of network structure, similar to that supported by saturated approaches. Using racial interaction of university undergraduates as an empirical example, the paper examines whether and to what extent racial diversity at the institutional level is reflected as racial integration at the interpersonal level by testing hypotheses regarding the quantity and quality of cross-race friendships. The primary goal of this article, however, is to introduce RDS to the network community and to stimulate further research toward the goal of expanding the analytical capacity of RDS. Advantages, limitations, and areas for future research to network analysis using RDS are discussed.     

Using respondent-driven sampling with ‘hard to reach’ marginalised young people: problems with slow recruitment and small network size

This paper documents an experience of using respondent-driven sampling (RDS) to recruit socially marginalised young people in Sydney, Australia. Respondents were young people aged 16–24?years who were current illicit drug users and who reported at least one feature of social marginalisation (e.g. recent homelessness or juvenile detention). Four seeds initiated the sampling and 61 respondents were recruited until the sampling was closed due to slow progress at week nine. The paper examines: (1) the overall success of RDS and compares this with similar RDS studies; and (2) the sufficiency of network ties among respondents. The analyses suggest that RDS was generally successful in that, despite its small size, the sample achieved adequately long recruitment chains and variables converged to equilibrium. Nevertheless, recruitment was much slower than comparable studies. This could be due to the study population having reduced willingness to participate, a high proportion of respondents who did not fit the selection criteria, and small and disparate networks. Using RDS with marginalised youth may require generous resourcing to allow large incentives to increase willingness, and a lengthy recruitment period. Moreover, the small networks suggest that researchers should start the sampling with a large number of seeds.     

Linked Ego Networks: Improving estimate reliability and validity with respondent-driven sampling

Respondent-driven sampling (RDS) is currently widely used for the study of HIV/AIDS-related high risk populations. However, recent studies have shown that traditional RDS methods are likely to generate large variances and may be severely biased since the assumptions behind RDS are seldom fully met in real life. To improve estimation in RDS studies, we propose a new method to generate estimates with ego network data, which is collected by asking respondents about the composition of their personal networks, such as “what proportion of your friends are married?”. By simulations on an extracted real-world social network of gay men as well as on artificial networks with varying structural properties, we show that the precision of estimates for population characteristics is greatly improved. The proposed estimator shows superior advantages over traditional RDS estimators, and most importantly, the method exhibits strong robustness to the recruitment preference of respondents and degree reporting error, which commonly happen in RDS practice and may generate large estimate biases and errors for traditional RDS estimators. The positive results henceforth encourage researchers to collect ego network data for variables of interests by RDS, for both hard-to-access populations and general populations when random sampling is not applicable.     

Ties,sites and irregularities: pitfalls and benefits in using respondent-driven sampling for surveying a homeless population

Respondent-driven sampling (RDS) is a survey method for hidden populations and, as such, it offers a suitable approach for sampling the homeless. Surprisingly, the practical use of RDS in surveying homeless populations has only sporadically been described in the professional literature so far, and the specifics of using RDS for sampling this group have not been reflected in depth. The goal of the article is to investigate how three specific concerns, namely the transitional character of social ties among the homeless, problems with locating the interview site, and the irregular use of coupons, affect the sampling process. The findings of the article are based on experience using RDS for creating two independent samples of homeless persons in two Czech cities. Worries of poor referral effectiveness were disproved, but poor validity of the network size indicator, tendency towards irregular use of coupons, and negative effects arising from selecting service centres for the homeless as survey sites were confirmed.     

Tailoring Organizational Characteristics for Empowerment

ABSTRACT

Empowerment is an important value orientation and intervention approach in social work and other disciplines. Viewed from an ecological perspective, a good fit between organizational characteristics and the life circumstances of individuals should provide empowerment benefits. By studying interaction effects of material resources and organizational characteristics on empowerment, this research sought to extend understanding of empowerment dynamics in community organizations. Using hierarchical regression analyses to investigate socio-economic status (SES) in a moderator model, findings of the study demonstrated that, among a diverse group of participants in two different faith-based community organizations, perceptions of organizational characteristics were more strongly related to empowerment for participants of lower SES. A substantive implication of the study is that community practitioners should attend to the fit between specific organizational processes and economic circumstances of community based organization participants. Strategies weighted toward attention to relationships among members linked to availability of and participation in a variety of organizational roles may be more salient for empowerment of the disadvantaged. Our findings are consistent with an ecological orientation to empowerment, and they add further support to the importance of ecological specificity in empowerment theory.     

Statistical adjustment of network degree in respondent-driven sampling estimators: Venue attendance as a proxy for network size among young MSM

We introduce a new venue-informed network degree measure, which we applied to respondent-driven sampling (RDS) estimators. Using data collected from 746 young MSM in 2014–2016 in Chicago, IL, and Houston, TX, we estimated the population seroprevalence of HIV and syphilis and risk/protective behaviors, using RDS estimates with self-reported network size as a standard degree measure as well as our proposed venue-informed degree measure. The results indicate that the venue-informed degree measure tended to be more efficient (smaller variance) and less biased than the other measure in both cities sampled. Venue attendance-adjusted network size may provide a more reliable and accurate degree measure for RDS estimates of the outcomes of interest.     

EXTENSIONS OF RESPONDENT-DRIVEN SAMPLING: ANALYZING CONTINUOUS VARIABLES AND CONTROLLING FOR DIFFERENTIAL RECRUITMENT

Respondent-driven sampling (RDS) is a network-based method for sampling hidden and hard-to-reach populations that has been shown to produce asymptotically unbiased population estimates when its assumptions are satisfied. This includes resolving a major concern regarding bias in chain-referral samples—that is, producing a population estimate that is independent of the seeds (initial subjects) with which sampling began. However, RDS estimates are limited to nominal variables, and one of the assumptions required for the proof of lack of bias is the absence of differential recruitment. One aim of this paper is to analyze the role of differential recruitment, quantify the bias it produces, and propose a new estimator that controls for it. The second aim is to extend RDS so that it can be employed to analyze continuous variables in a manner that controls for differential recruitment. The third aim is to describe means for carrying out multivariate analyses using RDS data. The analyses employ data from an RDS sample of 264 jazz musicians in the greater New York metropolitan area, taken in 2002.     

Respondent-Driven Sampling: An Assessment of Current Methodology

Respondent-Driven Sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure to expand the sample and reduce its dependence on the initial (convenience) sample.The current estimators of population averages make strong assumptions in order to treat the data as a probability sample. We evaluate three critical sensitivities of the estimators: to bias induced by the initial sample, to uncontrollable features of respondent behavior, and to the without-replacement structure of sampling.Our analysis indicates: (1) that the convenience sample of seeds can induce bias, and the number of sample waves typically used in RDS is likely insufficient for the type of nodal mixing required to obtain the reputed asymptotic unbiasedness; (2) that preferential referral behavior by respondents leads to bias; (3) that when a substantial fraction of the target population is sampled the current estimators can have substantial bias.This paper sounds a cautionary note for the users of RDS. While current RDS methodology is powerful and clever, the favorable statistical properties claimed for the current estimates are shown to be heavily dependent on often unrealistic assumptions. We recommend ways to improve the methodology.     

Conducting research on violence in Asian American communities: methodological issues

Conducting culturally competent research is a challenge as the United States becomes increasingly multicultural. When conducting research on violence in Asian American communities, researchers need to consider how culture, race, and ethnicity influence definitions of concepts, and methodological issues such as research designs, sampling, developing and translating instruments, ethical issues, recruiting research participants, supervising and training interviewers, and disseminating findings. Examples from the authors' research studies on community violence in the Khmer community, domestic violence in the Chinese American community, and dating violence in Asian American groups are extrapolated to highlight various themes. A commitment to a research program that collaborates with the community under study and cultural experts is vital at every stage of the research process.     

Home is where the heart is: Latinx youth expression and identity in a critical maker project

ABSTRACT

Making has been touted for its potential to democratize STEM yet could be replicating issues of limited participation of persons from educationally underserved populations. This version of making could be problematic for young women of color, limiting participation and aspirations for STEM careers. We present a counterexample with Critical Making, an approach of action, reflection, and community dialog to promote social change. We examine a multimedia design and implementation project as an expression of seven young Latinx¹ women’s experiences. Participants were tasked with creating a maker artifact to display data from a community survey and produced an interactive (touch capacitive) heart-shaped word cloud capturing positive qualities of their community. We utilized cultural-historical activity theory to focus on relations of the teen participants, meanings conveyed by the word cloud, and how digital tools interacted with norms, division of labor, and community relationships to mediate understanding. We report tensions between group versus community values and between possible design features and tool limitations. We also report how participants authored intersecting identities as makers, group members, and contributors to their community. Our results document the dynamics of a Critical Maker program and expand understanding of how young Latinx women experience making and STEM learning.     

Evolutionary Process of Social Capital Formation through Community Currency Organizations: The Japanese Case

Community currency systems are said to influence the revival of communities by promoting either local economic growth or social capital accumulation. However, no empirical studies have examined the multiple competing mechanisms for providing social support through transactional networks among participants. The current study connects network structural concepts to theories of social capital, transaction costs, homophily, and resource dependency at multiple levels and evaluates transactional relationships for community rebuilding and local economic development. We examine the evolutionary process of dynamic networks among local residents or organization members with network configurations in one of the largest Japanese community currency systems, “Peanuts.” Using longitudinal network data over 12 years for approximately 1400 actors, we conclude that the evolution and achievement of transactional network dynamics and partner selections differ between the two groups of participants: individual members and organization members. We also provide practical implications for sustaining participants’ transactions and commitment.     

Evaluating the Quality of Online Survey Data Collected in 2018 in the USA: Univariate,Bivariate, and Multivariate Analyses

Collecting survey data in Japan and the USA is difficult for many reasons, including the difficulty of creating complete sampling frames and low response rates. Online surveys, which collect data through online access panels and recruit members using nonprobability sampling, is becoming a popular alternative to traditional survey techniques, both in market and social science research. However, sociological researchers are hesitant to adopt online survey data collection techniques as it is unclear how representative such data are. This article examines the quality of online survey data by comparing online surveys with the two datasets collected using probability sampling, the American Community Survey and the General Social Survey. We conducted univariate, bivariate, and multivariate analyses and investigated whether similarities improve from the univariate analyses to bivariate relationships, and to bivariate relationships with controls. The results show that similarities improved from univariate to bivariate and multivariate analyses, but the results of bivariate and multivariate analyses did not differ. We concluded that data collected via volunteer‐based access panels yielded similar results to the benchmark data, especially when the relationships among variables are examined. We argue that automatically discrediting the data collected via volunteer‐based access panels is not good practice. With careful considerations of data quality, online survey data with nonprobability sampling could advance sociological research by giving researchers more freedom to ask questions at a relatively low cost, with a quick turnaround time, and more opportunities to conduct cross‐national research.     

AN EMPIRICAL TEST OF RESPONDENT-DRIVEN SAMPLING: POINT ESTIMATES, VARIANCE, DEGREE MEASURES, AND OUT-OF-EQUILIBRIUM DATA

This paper, which is the first large-scale application of respondent-driven sampling (RDS) to nonhidden populations, tests three factors related to RDS estimation against institutional data using two WebRDS samples of university undergraduates. First, two methods of calculating RDS point estimates are compared. RDS estimates calculated using both methods coincide closely, but variance estimation, especially for small groups, is problematic for both methods. In one method, the bootstrap algorithm used to generate confidence intervals is found to underestimate variance. In the other method, where analytical variance estimation is possible, confidence intervals tend to overestimate variance. Second, RDS estimates are found to be robust against varying measures of individual degree. Results suggest the standard degree measure currently employed in most RDS studies is among the best-performing degree measures. Finally, RDS is found to be robust against the inclusion of out-of-equilibrium data. The results show that valid point estimates can be generated with RDS analysis using real data, but that further research is needed to improve variance estimation techniques.     

Supporting people with intellectual disabilities to take part in focus groups: reflections on a research project

This paper discusses how support offered to people with intellectual disabilities who take part in research might affect the resultant data. People with intellectual disabilities from a long‐stay hospital, a day centre and a self‐advocacy group, all in the UK, participated in focus groups during a research project on nurse advocacy. Their supporters were staff employed by those services who were familiar with and to the group members. The support given to participants reflected the ethos of the services involved, relating either to the medical or the social model of disability. The paper argues that the philosophy of care influencing supporters of research participants with intellectual disabilities may have profound effects on the support provided. It may facilitate or inhibit open exchange of information. It may also aid clarification or cause contamination of the resultant data.     

Exploring the unmet needs for creating an enabling environment for nurturing care to promote migrant child health in Bishkek,Kyrgyzstan: A theory-guided community-based participatory action research

Empirical evidence on community-driven child health promotion programs in disadvantaged migrant populations is limited despite various promotional strategies. Therefore, we implemented a developmental process to shape child health interventions using theory-guided community-based participatory action research (CBPAR) in a migrant community in Bishkek, Kyrgyzstan between 2015 and 2019.The collaborative and iterative CBPAR process was conducted through participatory workshops and focus group discussions with support from trusting and collegial partnerships between community members and the research team. The goal and scope of the intervention was guided by enabling environments for nurturing care, including the four domains of caregivers’ capabilities, empowered communities, supportive services, and enabling policies. Diverse interests and needs identified by community members were aggregated in the theoretical model and reflected in the intervention.Community-driven intervention is perceived as a culturally acceptable, sustainable, sensitive and relevant approach to solve problems. There are several challenges in conducting the CBPAR, such as the effort and time spent on building partnerships, co-learning and mutual understanding, and the power equilibrium involved. Despite this, the success of the CBPAR process provided opportunities for community mobilization, empowerment and sustainability of the intervention. Evaluation of the process and outcomes of the intervention provided community health researchers and practitioners with evidence of the theory-guided community participatory approach.     

The Gudaga Research Program: A Case Study in Undertaking Research with an Urban Aboriginal Community

This paper presents the Gudaga Research Program as a case study describing the practice principles used to implement a successful research partnership with an urban Aboriginal community in south-western Sydney. This is one of few papers that address research issues unique to working with urban Aboriginal communities, in which the Aboriginal culture of the community is not homogenous. The authors argue that the relationships between the researchers and key community members and research participants underpin the research success. Throughout, the authors show that ongoing processes to nurture and reaffirm these relationships are important and require ongoing investment. A proposed practice framework demonstrates the relationship between knowledge and understanding of Aboriginal history and culture, the underpinning values including trust, respect, and reciprocity, and shared skills and communication. Examples of how these were built into the research are provided. These are important skills that have application beyond the research process.     

Latino youth participation in community-based participatory research to reduce teen pregnancy disparities

BackgroundCommunity-based participatory research can provide a framework to build community capacity to do health equity research, particularly from community members who may not typically participate in research design and intervention.PurposeThe purpose of this paper is to describe a community-based coalition's partnership and engagement with Latino youth throughout the research process addressing health disparities in unintended teen pregnancy rates in a local community. Israel and colleagues' components of CBPR provide a framework to develop youth participation throughout the research process.MethodHigh school and college Latino youth participated in health equity research from community assessments to design an intervention and dissemination of results.ResultsWorking with youth can improve the integrity and validity of the research process and can also provide benefits to the community and individual youth members, resulting in increased community capacity for health equity research.DiscussionLessons learned about the direct and indirect benefits and challenges are presented. Community-based partnerships working with youth should consider documenting the individual and collective impact of community engagement on the youth from the onset of participation.