Designing Effective Web Surveys is a practical guide to designing web surveys, based on empirical evidence and grounded in scientific research and theory. It is designed to guide survey practitioners ...in the art and science of developing and deploying successful web surveys. The author guides the researcher through the steps involved, from the basic building blocks and suggests ways to increase visual impact and interactivity. Throughout, he considers the importance of layout and design, and attention is also given to the way questions are put together. The book is intended for academic, government, and market researchers who design and conduct web surveys.
InEthnography in Today's World, Roger Sanjek examines the genre and practice of ethnography from a historical perspective, from its nineteenth-century beginnings and early twentieth-century ...consolidation, through political reorientations during the 1960s and the impact of feminism and postmodernism in later decades, to its current outlook in an increasingly urban world. Drawing on a career of ethnographic research across Brazil, Ghana, New York City, and with the Gray Panthers, Sanjek probes politics and rituals in multiethnic New York, the dynamics of activist meetings, human migration through the ages, and shifting conceptions of race in the United States. He interrogates well-known works from Boas, Whyte, Fabian, Geertz, Marcus, and Clifford, as well as less celebrated researchers, addressing methodological concerns from ethnographers' reliance on assistants in the formative days of the discipline to contemporary comparative issues and fieldwork and writing strategies.
Ethnography in Today's Worldcontributes to our understanding of culture and society in an age of globalization. These provocative examinations of the value of ethnographic research challenge conventional views as to how ethnographic fieldwork is and can be conceived, conducted, contextualized, and communicated to academic audiences and the twenty-first-century public.
Representation in Scientific Practice, published by the MIT Press in 1990, helped coalesce a long-standing interest in scientific visualization among historians, philosophers, and sociologists of ...science and remains a touchstone for current investigations in science and technology studies. This volume revisits the topic, taking into account both the changing conceptual landscape of STS and the emergence of new imaging technologies in scientific practice. It offers cutting-edge research on a broad array of fields that study information as well as short reflections on the evolution of the field by leading scholars, including some of the contributors to the 1990 volume. The essays consider the ways in which viewing experiences are crafted in the digital era; the embodied nature of work with digital technologies; the constitutive role of materials and technologies -- from chalkboards to brain scans -- in the production of new scientific knowledge; the metaphors and images mobilized by communities of practice; and the status and significance of scientific imagery in professional and popular culture.ContributorsMorana Alac, Michael Barany, Anne Beaulieu, Annamaria Carusi, Catelijne Coopmans, Lorraine Daston, Sarah de Rijcke, Joseph Dumit, Emma Frow, Yann Giraud, Aud Sissel Hoel, Martin Kemp, Bruno Latour, John Law, Michael Lynch, Donald MacKenzie, Cyrus Mody, Natasha Myers, Rachel Prentice, Arie Rip, Martin Ruivenkamp, Lucy Suchman, Janet Vertesi, Steve Woolgar
Abstract Background Advances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability ...of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time. Methods We develop MIDASim (MIcrobiome DAta Simulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, a generalized gamma distribution is used in place of the empirical distribution. Results We demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PERMANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model. Conclusions MIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods, at both the presence-absence level and the relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets.
Priority setting of health interventions is often ad-hoc and resources are not used to an optimal extent. Underlying problem is that multiple criteria play a role and decisions are complex. ...Interventions may be chosen to maximize general population health, to reduce health inequalities of disadvantaged or vulnerable groups, ad/or to respond to life-threatening situations, all with respect to practical and budgetary constraints. This is the type of problem that policy makers are typically bad at solving rationally, unaided. They tend to use heuristic or intuitive approaches to simplify complexity, and in the process, important information is ignored. Next, policy makers may select interventions for only political motives. This indicates the need for rational and transparent approaches to priority setting. Over the past decades, a number of approaches have been developed, including evidence-based medicine, burden of disease analyses, cost-effectiveness analyses, and equity analyses. However, these approaches concentrate on single criteria only, whereas in reality, policy makers need to make choices taking into account multiple criteria simultaneously. Moreover, they do not cover all criteria that are relevant to policy makers. Therefore, the development of a multi-criteria approach to priority setting is necessary, and this has indeed recently been identified as one of the most important issues in health system research. In other scientific disciplines, multi-criteria decision analysis is well developed, has gained widespread acceptance and is routinely used. This paper presents the main principles of multi-criteria decision analysis. There are only a very few applications to guide resource allocation decisions in health. We call for a shift away from present priority setting tools in health--that tend to focus on single criteria--towards transparent and systematic approaches that take into account all relevant criteria simultaneously.
The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define ...the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assunção for detecting noncircular clusters is shown to detect a cluster of very irregular shape that is much larger than the true cluster in our experiences.
We propose a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Monte Carlo simulation by considering several circular and noncircular hot-spot cluster models. For comparison, we also propose a new bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster.
The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one.
The proposed spatial scan statistic is shown to work well for small to moderate cluster size, up to say 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.
This open access textbook offers a practical guide into research ethics for undergraduate students in the social sciences. A step-by-step approach of the most viable issues, in-depth discussions of ...case histories and a variety of didactical tools will aid the student to grasp the issues at hand and help him or her develop strategies to deal with them. This book addresses problems and questions that any bachelor student in the social sciences should be aware of, including plagiarism, data fabrication and other types of fraud, data augmentation, various forms of research bias, but also peer pressure, issues with confidentiality and questions regarding conflicts of interest. Cheating, ‘free riding’, and broader issues that relate to the place of the social sciences in society are also included. The book concludes with a step-by-step approach designed to coach a student through a research application process.
Poorly preserved biological tissues have become an important source of DNA for a wide range of zoological studies. Measuring the quality of DNA obtained from these samples is often desired; however, ...there are no widely used techniques available for quantifying damage in highly degraded DNA samples. We present a general method that can be used to determine the frequency of polymerase blocking DNA damage in specific gene-regions in such samples. The approach uses quantitative PCR to measure the amount of DNA present at several fragment sizes within a sample. According to a model of random degradation the amount of available template will decline exponentially with increasing fragment size in damaged samples, and the frequency of DNA damage (lambda) can be estimated by determining the rate of decline.
The method is illustrated through the analysis of DNA extracted from sea lion faecal samples. Faeces contain a complex mixture of DNA from several sources and different components are expected to be differentially degraded. We estimated the frequency of DNA damage in both predator and prey DNA within individual faecal samples. The distribution of fragment lengths for each target fit well with the assumption of a random degradation process and, in keeping with our expectations, the estimated frequency of damage was always less in predator DNA than in prey DNA within the same sample (mean lambda(predator) = 0.0106 per nucleotide; mean lambda(prey) = 0.0176 per nucleotide). This study is the first to explicitly define the amount of template damage in any DNA extracted from faeces and the first to quantify the amount of predator and prey DNA present within individual faecal samples.
We present an approach for characterizing mixed, highly degraded PCR templates such as those often encountered in ecological studies using non-invasive samples as a source of DNA, wildlife forensics investigations and ancient DNA research. This method will allow researchers to measure template quality in order to evaluate alternate sources of DNA, different methods of sample preservation and different DNA extraction protocols. The technique could also be applied to study the process of DNA decay.
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