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Utilizing the most recent developments in statistical modeling as applied to population studies, the authors interpret results obtained from available software and apply these results to current research issues.
Although I feel honored to write a foreword for this important book, it is a task that I approach with some trepidation. The topics covered in the book summarize the current state of the art in technical demography. However, my knowledge and expertise with respect to technical demography are limited to the most fundamental and intermediate-level methods; hence, critical commentary on the contents of this volume is beyond my scope in this fore word. Since I have some understanding of the logic and substantive aspects of the methods rather than the complicated mathematics used in describing them, my comments will necessarily be restricted to the book's general or ganization and content. To date, most texts published on technical demography have been limited to traditional demographic methods: sources and limitations of data, life table construction and applications, standardization techniques, various methods for preparing population estimates and forecasts, etc. However, population specialists have in recent years been developing and successfully applying a variety of sophisticated techniques not covered in the more standard intro ductory texts. In addition, many traditional methods that are unique to the demographic discipline have been improved and extended.
Wildlife Demography compiles the multitude of available estimation techniques based on sex and age data, and presents these varying techniques in one organized, unified volume. Designed to guide researchers to the most appropriate estimator based upon their particular data set and the desired level of study precision, this book provides quantitative consideration, statistical models, estimator variance, assumptions and examples of use. The authors focus on estimation techniques using sex and age ratios because this data is relatively easy to collect and commonly used by wildlife management. - Applicable to a wide array of wildlife species, including game and non-game birds and mammals - Features more than 100 annotated examples illustrating application of statistical methods - Includes more than 640 references of the analysis of nontagging data and the factors that may influence interpretation - Derives historical and ad hoc demographic methods in a modern statistical framework
The nature of demography; Rates and rations; Accuracy and error; The life table; The study of mortality; Measurement of fertility; Growth of population; Migration and the distribution of population; Manpower and working activities.
The increasing diversity of population of the United States presents many challenges to conducting health research that is representative and informative. Dispersion and accessibility issues can increase logistical costs; populations for which it is difficult to obtain adequate sample size are also likely to be expensive to study. Hence, even if it is technically feasible to study a small population, it may not be easy to obtain the funding to do so. In order to address the issues associated with improving health research of small populations, the National Academies of Sciences, Engineering, and Medicine convened a workshop in January 2018. Participants considered ways of addressing the challenges of conducting epidemiological studies or intervention research with small population groups, including alternative study designs, innovative methodologies for data collection, and innovative statistical techniques for analysis.
This book introduces and describes four techniques, which are at the core of professional practice and education: The first technique , curve-fitting/extrapolation, projects an area' s population, employment, or other characteristics by identifying and extending historical trends. The second technique, the cohort-component technique, projects an area' s population by dividing it into a uniform set of population subgroups or cohorts and applying the three components of population change-mortality, fertility, and migration-to each cohort. The third technique, the economic base technique, projects local economic change by dividing a local economy into basic and nonbasic sectors and by focusing analytic attention on the basic sector. The fourth technique, the shift-share technique, projects an area's economic activity by relating it to the activity of the state or nation in which it is located.
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.
Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS, and its open-source sister OpenBugs, is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Comprehensive and richly commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologist All WinBUGS/OpenBUGS analyses are completely integrated in software R Includes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R