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Network sampling emerged as a set of methods for drawing statistically valid samples of hard-to-reach populations. The first form of network sampling, multiplicity sampling, involved asking respondents about events affecting those in their personal networks; it was subsequently applied to studies of homicide, HIV, and other topics, but its usefulness is limited to public events. Link-tracing designs employ a different approach to study hard-to-reach populations, using a set of respondents that expands in waves as each round of respondents recruit their peers. Link-tracing as applied to hidden populations, often described as snowball sampling, was initially considered a form of convenience sampling. This changed with the development of respondent-driven sampling (RDS), a widely used network sampling method in which the link-tracing design is adapted to provide the basis for statistical inference. The literature on RDS is large and rapidly expanding, involving contributions by numerous independent research groups employing data from dozens of different countries. Within this literature, many important research questions remain unresolved, including how best to choose among alternative RDS estimators, how to refine existing estimators to make them less dependent on assumptions that are sometimes counterfactual, and perhaps the greatest unresolved issue, how best to calculate the variability of the estimates.

A theory of public policy using a transaction space model of contractual analysis is outlined, an approach based on transaction cost economics, game theory, & the contractual paradigm that treats government activities, including statutes & the organizations that administer them, as long-term contracts negotiated to economize on the costs of decision making. Theodore Lowi's typology of public policies ("The State in Politics: The Relation between Policy and Administration," in Noll, Roger [Ed], Regulatory Politics and the Social Sciences, Berkeley: U of California Press, 1985) is drawn on to explain how government comes to be involved in some coercive activities & not others. Reasons why Lowi's typology appears to fit some policies well & be inadequate for others are explored. It is theorized that demand for government intervention arises when private problems of coordination, division, & defection -- each a distinct dimension of transaction space -- cannot be resolved. Lowi's typology best fits unidimensional problems; multidimensional problems are more complex but also consistent with the model. 3 Tables, 1 Figure, 51 References. Adapted from the source document.

The literature on drinking and drug use exhibits considerable fragmentation due to many researchers' practice of concentrating exclusively upon the use of a single substance, thus producing separate literatures specific to different drugs. Fragmentation of the literature has been further compounded by the use of distinct and incompatible theoretic perspectives which guide research efforts, and by the lack of attention to theoretic issues. A new theoretical perspective, a "unified perspective," is presented here and proposed as a common theoretical framework for researchers working in any substantive area of drug use. This perspective seeks to bridge conflict and consensus theory, and proposes a resolution of problems arising from several limitations and biases associated with these theoretical positions. An empirical application of the unified perspective is offered in support of its applicability and usefulness to drug use research.

A dilemma arises for researchers who sample hidden populations, such as injection drug users (IDUs), and use financial incentives to recruit respondents. To prevent respondent duplication (a subject participates in a study multiple times by using different identities) and respondent impersonation (a subject assumes the identity of other respondents), researchers must confirm their subjects' identities. Documentation, however, introduces sampling bias against those who lack such identification, or who wish to remain anonymous. Definitive forms of identification like photography and fingerprints introduce a bias against the more distrustful members of the population, and scanner-based biometrics can be expensive. Most research projects therefore rely on staff to recognize former respondents, but staff turnover and a large number of respondents compromise accuracy. We describe and assess quantitatively the accuracy of a method for subject identification based on a statistical principle, the interchangeability of indicators, in which multiple weak indicators combine to form a stronger aggregate measure. The analysis shows that observable indicators of identity (scars, birthmarks, tattoos, eye color, ethnicity, and gender) and five biometric measures (height, forearm lengths, and wrist widths) provide the basis for a reliable and easily administered method for subject identification.

Background Violent drug markets are not as prominent as they once were in the United States, but they still exist and are associated with significant crime and lower quality of life. The drug market intervention (DMI) is an innovative strategy that uses focused deterrence, community engagement, and incapacitation to reduce crime and disorder associated with these markets. Although studies show that DMI can reduce crime and overt drug activity, one perspective is prominently missing from these evaluations: those who purchase drugs. Objectives This study explores the use of respondent-driven sampling (RDS)—a statistical sampling method—to approximate a representative sample of drug users who purchased drugs in a targeted DMI market to gain insight into the effect of a DMI on market dynamics. Methods Using RDS, we recruited individuals who reported hard drug use (crack or powder cocaine, heroin, methamphetamine, or illicit use of prescriptions opioids) in the last month to participate in a survey. The main survey asked about drug use, drug purchasing, and drug market activity before and after DMI; a secondary survey asked about network characteristics and recruitment. Conclusions Our sample of 212 respondents met key RDS assumptions, suggesting that the characteristics of our weighted sample approximate the characteristics of the drug user network. The weighted estimates for market purchasers are generally valid for inferences about the aggregate population of customers, but a larger sample size is needed to make stronger inferences about the effects of a DMI on drug market activity.

AIDS prevention efforts for injection drug users (IDUs) since 1988 in over 60 inner-city areas within the United States have been based on a "provider-client" model called "street-based outreach." We document the research showing that these traditional outreach projects operate under conditions that cause hierarchy and supervision to break down easily. The result is an array of organizational problems that push outreach projects toward inertia, and invite high levels of mal- and nonperformance by outreach workers (OWs) as rational adaptations to their work conditions. Nevertheless, research has also documented that IDUs responded very impressively to the outreach services they received. Based on IDUs' responsiveness, we outline the operational features of a "Peer-Driven Intervention" (PDI) that relies on an active collaboration with IDUs in place of a "provider-client" model. Based on a comparative study in eastern Connecticut, we present preliminary impact data comparing the effectiveness of a PDI with a traditional outreach intervention in terms of recruitment power, educational effectiveness of IDUs in the community, and comparative intervention costs.