The Network Survival Method for Estimating Adult Mortality: Evidence From a Survey Experiment in Rwanda

Adult death rates are a critical indicator of population health and well-being. Wealthy countries have high-quality vital registration systems, but poor countries lack this infrastructure and must rely on estimates that are often problematic. In this article, we introduce the network survival method, a new approach for estimating adult death rates. We derive the precise conditions under which it produces consistent and unbiased estimates. Further, we develop an analytical framework for sensitivity analysis. To assess the performance of the network survival method in a realistic setting, we conducted a nationally representative survey experiment in Rwanda (n = 4,669). Network survival estimates were similar to estimates from other methods, even though the network survival estimates were made with substantially smaller samples and are based entirely on data from Rwanda, with no need for model life tables or pooling of data from other countries. Our analytic results demonstrate that the network survival method has attractive properties, and our empirical results show that this method can be used in countries where reliable estimates of adult death rates are sorely needed.     

Large scale communication networks—Design and analysis

The paper discusses the problem of design and analysis of large scale communication systems. An iterative process, composed of a minimum cost network design algorithm and a network performance algorithm, is presented for the solution of these problems. Computational considerations, using these algorithms, are discussed.     

Assessing the effectiveness of strategic planning

This paper describes a method for assessing the effectiveness of strategic planning systems in terms of the results actually observed subsequent to planning activity. The paper explains in particular how, in making the assessment, one might cope with the fact of environmental change subsequent to the setting of planned goals. This ends oriented approach to measuring effectiveness is shown to be complementary to process oriented approaches and is illustrated by an example from the coal industry.     

Improving homeless persons' utilisation of primary care: lessons to be learned from an outreach programme in The Netherlands

Elissen AMJ, Van Raak AJA, Derckx EWCC, Vrijhoef HJM. Improving homeless persons' utilisation of primary care: lessons to be learned from an outreach programme in The Netherlands Faced with rising homelessness, countries around the world are in need of innovative approaches to caring for those without shelter, who, more often than not, suffer from severe health problems. We conducted a case study of an innovative Dutch Primary Care for the Homeless (PCH) programme to gain insight into clients' demographic characteristics, health problems and service use, and to develop an explanation for its success in increasing the latter. Our analyses are based on a combination of quantitative and qualitative data. The results of the study suggest that the success of the PCH programme can be explained by the providers' pragmatism and will to adapt their mode of care provision to the behavioural patterns and needs of their homeless clients.     

Sampling and Estimation in Hidden Populations Using Respondent‐Driven Sampling

Standard statistical methods often provide no way to make accurate estimates about the characteristics of hidden populations such as injection drug users, the homeless, and artists. In this paper, we further develop a sampling and estimation technique called respondent‐driven sampling, which allows researchers to make asymptotically unbiased estimates about these hidden populations. The sample is selected with a snowball‐type design that can be done more cheaply, quickly, and easily than other methods currently in use. Further, we can show that under certain specified (and quite general) conditions, our estimates for the percentage of the population with a specific trait are asymptotically unbiased. We further show that these estimates are asymptotically unbiased no matter how the seeds are selected. We conclude with a comparison of respondent‐driven samples of jazz musicians in New York and San Francisco, with corresponding institutional samples of jazz musicians from these cities. The results show that some standard methods for studying hidden populations can produce misleading results.     

COMPARISON OF FEATURE SIGNIFICANCE QUANTILE APPROXIMATIONS

Curve estimates and surface estimates often contain features such as inclines, bumps or ridges which may signify an underlying structural mechanism. However, spurious features are also a common occurrence and it is important to identify those features that are statistically significant. A method has been developed recently for recognising feature significance based on the derivatives of the function estimate. It requires simultaneous confidence intervals and tests, which in turn require quantiles for the maximal deviation statistics. This paper reviews and compares various approximations to these quantiles. Applying upcrossing‐probability theory to this problem yields better quantile approximations than the use of an independent blocks method.     

The Game of Contacts: Estimating the Social Visibility of Groups

Estimating the sizes of hard-to-count populations is a challenging and important problem that occurs frequently in social science, public health, and public policy. This problem is particularly pressing in HIV/AIDS research because estimates of the sizes of the most at-risk populations-illicit drug users, men who have sex with men, and sex workers-are needed for designing, evaluating, and funding programs to curb the spread of the disease. A promising new approach in this area is the network scale-up method, which uses information about the personal networks of respondents to make population size estimates. However, if the target population has low social visibility, as is likely to be the case in HIV/AIDS research, scale-up estimates will be too low. In this paper we develop a game-like activity that we call the game of contacts in order to estimate the social visibility of groups, and report results from a study of heavy drug users in Curitiba, Brazil (n = 294). The game produced estimates of social visibility that were consistent with qualitative expectations but of surprising magnitude. Further, a number of checks suggest that the data are high-quality. While motivated by the specific problem of population size estimation, our method could be used by researchers more broadly and adds to long-standing efforts to combine the richness of social network analysis with the power and scale of sample surveys.