Books on the topic 'Targeted sampling'
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1
Ahrens, T. J. Planetary and primitive object strength measurements and sampling apparatus: NASA #NAGW 2439, final report; February 1, 1991 through January 31, 1997. Pasadena, Calif: California Institute of Technology, Seismological Laboratory, 1997.
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2
1963-, Mandrak Nicholas Edward, Canada. Dept. of Fisheries and Oceans., Great Lakes Laboratory for Fisheries and Aquatic Sciences., and Canada. Dept. of Fisheries and Oceans. Central and Arctic Region., eds. Targeted, wadeable sampling of fish species at risk in the Lake St. Clair watershed of southwestern Ontario, 2003. Burlington, Ont: Dept. of Fisheries and Oceans, 2006.
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3
Berry, Justin, Youssef Chouhoud, and Jane Junn. Reaching Beyond Low-Hanging Fruit. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.1.
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This chapter argues for the use of creative and targeted strategies rather than a one-size-fits-all approach to capturing information on low-incidence populations. It first conceptualizes low-incidence populations and highlights the existing empirical literature on them and then frames the challenges of polling these populations with an overview of sampling, contacting, and analytical strategies. It highlights the inherent trade-offs of each approach and points to the factors to consider when determining which strategy is best suited to particular research questions. It then details polling efforts designed to capture attitudes and behaviors of American Muslims, Asian Americans, and nonelected political activists. The chapter concludes with a discussion of fruitful polling practices for conducting research on low-incidence U.S. populations, arguing that the approach to polling these populations must be equally informed by the unique characteristics of the target group and the analytical conclusions one seeks to draw.
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Taberlet, Pierre, Aurélie Bonin, Lucie Zinger, and Eric Coissac. Sampling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.003.0004.
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Sampling is crucial to any ecological study. Chapter 4 “Sampling” aims at proving keys for a successful sampling campaign when using DNA metabarcoding. It first describes the origin, fate, and transport of environmental DNA in various environments, from freshwater streams to soils, and discusses the implication of the DNA cycle in the environment for answering ecological questions. The chapter presents guidelines to appropriately sample the target DNA population and maximize the representativeness of the retrieved ecological signal. Different sampling strategies at the level of the sampling area and sampling units are proposed for different environmental matrices and ecological questions. Sample storage methods maximizing the preservation of environmental DNA are also discussed.
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Hankin, David, Michael S. Mohr, and Kenneth B. Newman. Sampling Theory. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198815792.001.0001.
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We present a rigorous but understandable introduction to the field of sampling theory for ecologists and natural resource scientists. Sampling theory concerns itself with development of procedures for random selection of a subset of units, a sample, from a larger finite population, and with how to best use sample data to make scientifically and statistically sound inferences about the population as a whole. The inferences fall into two broad categories: (a) estimation of simple descriptive population parameters, such as means, totals, or proportions, for variables of interest, and (b) estimation of uncertainty associated with estimated parameter values. Although the targets of estimation are few and simple, estimates of means, totals, or proportions see important and often controversial uses in management of natural resources and in fundamental ecological research, but few ecologists or natural resource scientists have formal training in sampling theory. We emphasize the classical design-based approach to sampling in which variable values associated with units are regarded as fixed and uncertainty of estimation arises via various randomization strategies that may be used to select samples. In addition to covering standard topics such as simple random, systematic, cluster, unequal probability (stressing the generality of Horvitz–Thompson estimation), multi-stage, and multi-phase sampling, we also consider adaptive sampling, spatially balanced sampling, and sampling through time, three areas of special importance for ecologists and natural resource scientists. The text is directed to undergraduate seniors, graduate students, and practicing professionals. Problems emphasize application of the theory and R programming in ecological and natural resource settings.
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Gimpel, James G. Sampling for Studying Context. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.23.
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Using the example of Ohio and its media markets, this chapter discusses the geographic distribution of respondents resulting from alternative sampling schemes. Traditional survey research designs for gathering information on voter attitudes and behavior usually ignore variability in context in favor of representation of a target population. When sample sizes are large, these polls also provide reasonably accurate estimates for focal subgroups of the electoral population. As the examples here show, conventional polls frequently lack the variations in geographic context likely to matter most to understanding social environments and the interdependence among voters, limiting variation on such continua as urban and rural, economic equality and inequality, occupational differences, exposure to physical environmental conditions, and a variety of other factors that exhibit spatial variation. The chapter calls for more surveys that represent exposure to a broader range of social and physical environments than researchers have produced up to now.
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Berinsky, Adam J. Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias. Cambridge University Press, 2020.
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8
Caughey, Devin, Sara Chatfield, and Adam J. Berinskey. Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias. Cambridge University Press, 2020.
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9
Lapierre, Laurent M., and Alicia D. McMullan. A Review of Methodological and Measurement Approaches to the Study of Work and Family. Edited by Tammy D. Allen and Lillian T. Eby. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199337538.013.4.
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This chapter provides a review of research methods reported in work–family (WF) articles published in peer-reviewed journals between 2004 and 2013. Methodological issues addressed include sampling (sampling methods, identification of target and source populations, response rate, and comparison of sample to source population), research designs (time horizon, laboratory vs. field setting, and level of control), data collection methods, levels of analysis, use of multiple data sources, triangulation, and the use of objective outcome measures. When possible, statistical comparisons were made between the results of this review and those reported in an earlier review by Casper, Eby, Bordeaux, Lockwood, and Lambert (2007). Results show that multiwave as well as qualitative research designs have been used more frequently since the period reviewed by Casper and colleagues. Still, there is room for improvement in the methodological rigor with which WF research is undertaken. In particular, WF scholars are encouraged to give more attention to sampling-related considerations, and to more strongly consider the use of experimental research designs, data/measurement triangulation, and the collection of data beyond the individual level of analysis.
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Taberlet, Pierre, Aurélie Bonin, Lucie Zinger, and Eric Coissac. Environmental DNA for functional diversity. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.003.0010.
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Chapter 10 “Environmental DNA for functional diversity” discusses the potential of environmental DNA to assess functional diversity. It first focuses on DNA metabarcoding and discusses the extent to which this approach can be used and/or optimized to retrieve meaningful information on the functions of the target community. This knowledge usually involves coarsely defined functional groups (e.g., woody, leguminous, graminoid plants; shredders or decomposer soil organisms; pathogenicity or decomposition role of certain microorganisms). Chapter 10 then introduces metagenomics and metatranscriptomics approaches, their advantages, but also the challenges and solutions to appropriately sampling, sequencing these complex DNA/RNA populations. Chapter 10 finally presents several strategies and software to analyze metagenomes/metatranscriptomes, and discusses their pros and cons.
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Rayment, George E., and David J. Lyons. Soil Chemical Methods - Australasia. CSIRO Publishing, 2010. http://dx.doi.org/10.1071/9780643101364.
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Soil Chemical Methods – Australasia describes over 200 laboratory and field chemical tests relevant to Australasia and beyond. The information and methodology provided across 20 chapters is comprehensive, systematic, uniquely coded, up-to-date and designed to promote chemical measurement quality. There is guidance on the choice and application of analytical methods from soil sampling through to the reporting of results. In many cases, optional analytical ‘finishes’ are provided, such as flow-injection analysis, electro-chemistry, multiple flame technologies, and alternatives to chemical testing offered by near-range and mid-range infrared diffuse reflectance spectroscopy.
The book supersedes and updates the soil chemical testing section of the 1992 Australian Laboratory Handbook of Soil and Water Chemical Methods of Rayment and Higginson, while retaining method codes and other strengths of that Handbook. Chapters cover soil sampling, sample preparation and moisture content; electrical conductivity and redox potential; soil pH; chloride; carbon; nitrogen; phosphorus; sulphur; gypsum; micronutrients; extractable iron, aluminium and silicon; saturation extracts; ion-exchange properties; lime requirements; total miscellaneous elements; miscellaneous extractable elements; alkaline earth carbonates and acid sulfate soils. In addition, there are informative Appendices, including information on the accuracy and precision of selected methods.
This book targets practising analysts, laboratory managers, students, academics, researchers, consultants and advisors involved in the analysis, use and management of soils for fertility assessments, land use surveys, environmental studies and for natural resource management.
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Handbook of invasive plant-parasitic nematodes. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789247367.0000.
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Abstract This volume compiles and updates information on invasive plant-parasitic nematodes and their looming threat in different countries. It offers a global perspective on invasive nematodes by presenting 17 chapters with information on more than 100 nematodes and their potential threat in different countries. Each nematode entry includes information on: authentic identification; geographical distribution; risk of introduction; host ranges; symptoms; biology and ecology; planting material liable to carry the nematode(s) and its vector, if any; chance of establishment; likely impact; phytosanitary measures; and a detailed account of diagnosis procedures, such as sampling, isolation/detection and identification with morphological and molecular characterization. The aim of the book is to provide basic and advanced knowledge on invasive nematodes with a global perspective, and it targets practitioners, professionals, scientists, researchers, students and government officials working on plant quarantine and biosecurity with regard to plant-parasitic nematodes.
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Coolen, A. C. C., A. Annibale, and E. S. Roberts. Graphs with hard constraints: further applications and extensions. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0007.
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This chapter looks at further topics pertaining to the effective use of Markov Chain Monte Carlo to sample from hard- and soft-constrained exponential random graph models. The chapter considers the question of how moves can be sampled efficiently without introducing unintended bias. It is shown mathematically and numerically that apparently very similar methods of picking out moves can give rise to significant differences in the average topology of the networks generated by the MCMC process. The general discussion in complemented with pseudocode in the relevant section of the Algorithms chapter, which explicitly sets out some accurate and practical move sampling approaches. The chapter also describes how the MCMC equilibrium probabilities can be purposely deformed to, for example, target desired correlations between degrees of connected nodes. The mathematical exposition is complemented with graphs showing the results of numerical simulations.
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Burns, Tom, and Mike Firn. Research and development. Edited by Tom Burns and Mike Firn. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198754237.003.0029.
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This chapter covers the spectrum of routine monitoring, audit, service evaluation, and formal research. Routine monitoring is an essential task for all mental health professionals, and techniques to make it more palatable are explored, including using routine data for clinical supervision and monitoring team targets. Regular audit is described as an essential tool for logical service development and quality improvement. In the discussion of research, the importance of choosing the correct methodology and of paying attention to detail are stressed. In community psychiatry, sampling bias, regression to the mean, and the Hawthorne effect pose important risks. The hierarchy of research methods is outlined with randomized controlled trials (RCTs) at the top, preferably with either single- or double-blinding. Careful statistics and systematic reviews support evidence-based practice. In addition to experimental quantitative trials, there is a place for cohort and case control trials, as well as for qualitative trials to generate hypotheses.
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Anderson, Raymond A. Credit Intelligence & Modelling. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192844194.001.0001.
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This book, “Forest Paths” for short, started as a detailed guide for the construction of predictive models for credit and other risk assessment, for use in big-bank retail lending. It became a textbook covering credit processes (from marketing through to fraud), bureau and rating agencies, and various tools. Included are detailed histories (economics, statistics, social science}, which much referencing. It is unique in the field, with chatpers’-end questions. The primary target market is corporate and academic, but much would be of interest to a broader audience. There are eight modules: 1) an introduction to credit risk assessment and predictive modelling; 2) micro-histories of credit, credit intelligence, credit scoring, plus industrial revolutions, economic ups and downs, and both personal registration and identification; 4) mathematical and statistical tools used to develop and assess predictive models; 5) project management and data assembly; 6) data preparation from sampling to reject inference; 7) model training through to implementation; and 8) appendices, including an extensive glossary, bibliography, and index. Although the focus is credit risk, especially in the retail consumer and small-business segments, many concepts are common across disciplines as diverse as psychology, biology, engineering, and computer science, whether academic research or practical use. It also covers issues relating to the use of machine learning for credit risk assessment. Most of the focus is on traditional modelling techniques, but the increasing use of machine learning is recognised, as are its limitations. It is hoped that the contents will inform both camps.