Author: David A. Swanson
Publisher: Springer Science & Business Media
ISBN: 9048189543
Category : Social Science
Languages : en
Pages : 420
Book Description
Providing a unified and comprehensive treatment of the theory and techniques of sub-national population estimation, this much-needed publication does more than collate disparate source material. It examines hitherto unexplored methodological links between differing types of estimation from both the demographic and sample-survey traditions and is a self-contained primer that combines academic rigor with a wealth of real-world examples that are useful models for demographers. Between censuses, which are expensive, administratively complex, and thus infrequent, demographers and government officials must estimate population using either demographic modeling techniques or statistical surveys that sample a fraction of residents. These estimates play a central role in vital decisions that range from funding allocations and rate-setting to education, health and housing provision. They also provide important data to companies undertaking market research. However, mastering small-area and sub-national population estimation is complicated by scattered, incomplete and outdated academic sources—an issue this volume tackles head-on. Rapidly increasing population mobility is making inter-census estimation ever more important to strategic planners. This book will make the theory and techniques involved more accessible to anyone with an interest in developing or using population estimates.
Subnational Population Estimates
Author: David A. Swanson
Publisher: Springer Science & Business Media
ISBN: 9048189543
Category : Social Science
Languages : en
Pages : 420
Book Description
Providing a unified and comprehensive treatment of the theory and techniques of sub-national population estimation, this much-needed publication does more than collate disparate source material. It examines hitherto unexplored methodological links between differing types of estimation from both the demographic and sample-survey traditions and is a self-contained primer that combines academic rigor with a wealth of real-world examples that are useful models for demographers. Between censuses, which are expensive, administratively complex, and thus infrequent, demographers and government officials must estimate population using either demographic modeling techniques or statistical surveys that sample a fraction of residents. These estimates play a central role in vital decisions that range from funding allocations and rate-setting to education, health and housing provision. They also provide important data to companies undertaking market research. However, mastering small-area and sub-national population estimation is complicated by scattered, incomplete and outdated academic sources—an issue this volume tackles head-on. Rapidly increasing population mobility is making inter-census estimation ever more important to strategic planners. This book will make the theory and techniques involved more accessible to anyone with an interest in developing or using population estimates.
Publisher: Springer Science & Business Media
ISBN: 9048189543
Category : Social Science
Languages : en
Pages : 420
Book Description
Providing a unified and comprehensive treatment of the theory and techniques of sub-national population estimation, this much-needed publication does more than collate disparate source material. It examines hitherto unexplored methodological links between differing types of estimation from both the demographic and sample-survey traditions and is a self-contained primer that combines academic rigor with a wealth of real-world examples that are useful models for demographers. Between censuses, which are expensive, administratively complex, and thus infrequent, demographers and government officials must estimate population using either demographic modeling techniques or statistical surveys that sample a fraction of residents. These estimates play a central role in vital decisions that range from funding allocations and rate-setting to education, health and housing provision. They also provide important data to companies undertaking market research. However, mastering small-area and sub-national population estimation is complicated by scattered, incomplete and outdated academic sources—an issue this volume tackles head-on. Rapidly increasing population mobility is making inter-census estimation ever more important to strategic planners. This book will make the theory and techniques involved more accessible to anyone with an interest in developing or using population estimates.
Big Data Meets Survey Science
Author: Craig A. Hill
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784
Book Description
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784
Book Description
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
Introduction to Small Area Estimation Techniques
Author: Asian Development Bank
Publisher: Asian Development Bank
ISBN: 9292622234
Category : Business & Economics
Languages : en
Pages : 152
Book Description
This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.
Publisher: Asian Development Bank
ISBN: 9292622234
Category : Business & Economics
Languages : en
Pages : 152
Book Description
This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.
Small-Area Estimates of School-Age Children in Poverty
Author: Constance F. Citro
Publisher:
ISBN: 9780585085012
Category : Children
Languages : en
Pages : 186
Book Description
Publisher:
ISBN: 9780585085012
Category : Children
Languages : en
Pages : 186
Book Description
Small Area Estimation
Author: J. N. K. Rao
Publisher: John Wiley & Sons
ISBN: 0471431621
Category : Mathematics
Languages : en
Pages : 340
Book Description
An accessible introduction to indirect estimation methods, both traditional and model-based. Readers will also find the latest methods for measuring the variability of the estimates as well as the techniques for model validation. Uses a basic area-level linear model to illustrate the methods Presents the various extensions including binary response data through generalized linear models and time series data through linear models that combine cross-sectional and time series features Provides recent applications of SAE including several in U.S. Federal programs Offers a comprehensive discussion of the design issues that impact SAE
Publisher: John Wiley & Sons
ISBN: 0471431621
Category : Mathematics
Languages : en
Pages : 340
Book Description
An accessible introduction to indirect estimation methods, both traditional and model-based. Readers will also find the latest methods for measuring the variability of the estimates as well as the techniques for model validation. Uses a basic area-level linear model to illustrate the methods Presents the various extensions including binary response data through generalized linear models and time series data through linear models that combine cross-sectional and time series features Provides recent applications of SAE including several in U.S. Federal programs Offers a comprehensive discussion of the design issues that impact SAE
Small-area Population Estimates--methods and Their Accuracy and New Metropolitan Area Definitions and Their Impact on the Private and Public Sector
Author:
Publisher:
ISBN:
Category : Demographic surveys
Languages : en
Pages : 92
Book Description
Publisher:
ISBN:
Category : Demographic surveys
Languages : en
Pages : 92
Book Description
Hierarchical Modeling and Inference in Ecology
Author: J. Andrew Royle
Publisher: Elsevier
ISBN: 0080559255
Category : Science
Languages : en
Pages : 463
Book Description
A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution* abundance models based on many sampling protocols, including distance sampling* capture-recapture models with individual effects* spatial capture-recapture models based on camera trapping and related methods* population and metapopulation dynamic models* models of biodiversity, community structure and dynamics - Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) - Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis - Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS - Computing support in technical appendices in an online companion web site
Publisher: Elsevier
ISBN: 0080559255
Category : Science
Languages : en
Pages : 463
Book Description
A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution* abundance models based on many sampling protocols, including distance sampling* capture-recapture models with individual effects* spatial capture-recapture models based on camera trapping and related methods* population and metapopulation dynamic models* models of biodiversity, community structure and dynamics - Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) - Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis - Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS - Computing support in technical appendices in an online companion web site
Small Populations, Large Effects
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309255635
Category : Social Science
Languages : en
Pages : 176
Book Description
In the early 1990s, the Census Bureau proposed a program of continuous measurement as a possible alternative to the gathering of detailed social, economic, and housing data from a sample of the U.S. population as part of the decennial census. The American Community Survey (ACS) became a reality in 2005, and has included group quarters (GQ)-such places as correctional facilities for adults, student housing, nursing facilities, inpatient hospice facilities, and military barracks-since 2006, primarily to more closely replicate the design and data products of the census long-form sample. The decision to include group quarters in the ACS enables the Census Bureau to provide a comprehensive benchmark of the total U.S. population (not just those living in households). However, the fact that the ACS must rely on a sample of what is a small and very diverse population, combined with limited funding available for survey operations, makes the ACS GQ sampling, data collection, weighting, and estimation procedures more complex and the estimates more susceptible to problems stemming from these limitations. The concerns are magnified in small areas, particularly in terms of detrimental effects on the total population estimates produced for small areas. Small Populations, Large Effects provides an in-depth review of the statistical methodology for measuring the GQ population in the ACS. This report addresses difficulties associated with measuring the GQ population and the rationale for including GQs in the ACS. Considering user needs for ACS data and of operational feasibility and compatibility with the treatment of the household population in the ACS, the report recommends alternatives to the survey design and other methodological features that can make the ACS more useful for users of small-area data.
Publisher: National Academies Press
ISBN: 0309255635
Category : Social Science
Languages : en
Pages : 176
Book Description
In the early 1990s, the Census Bureau proposed a program of continuous measurement as a possible alternative to the gathering of detailed social, economic, and housing data from a sample of the U.S. population as part of the decennial census. The American Community Survey (ACS) became a reality in 2005, and has included group quarters (GQ)-such places as correctional facilities for adults, student housing, nursing facilities, inpatient hospice facilities, and military barracks-since 2006, primarily to more closely replicate the design and data products of the census long-form sample. The decision to include group quarters in the ACS enables the Census Bureau to provide a comprehensive benchmark of the total U.S. population (not just those living in households). However, the fact that the ACS must rely on a sample of what is a small and very diverse population, combined with limited funding available for survey operations, makes the ACS GQ sampling, data collection, weighting, and estimation procedures more complex and the estimates more susceptible to problems stemming from these limitations. The concerns are magnified in small areas, particularly in terms of detrimental effects on the total population estimates produced for small areas. Small Populations, Large Effects provides an in-depth review of the statistical methodology for measuring the GQ population in the ACS. This report addresses difficulties associated with measuring the GQ population and the rationale for including GQs in the ACS. Considering user needs for ACS data and of operational feasibility and compatibility with the treatment of the household population in the ACS, the report recommends alternatives to the survey design and other methodological features that can make the ACS more useful for users of small-area data.
Using the American Community Survey
Author: Constance F. Citro
Publisher:
ISBN:
Category : Reference
Languages : en
Pages : 360
Book Description
The American Community Survey (ACS) is a major new initiative from the U.S. Census Bureau designed to provide continuously updated information on the numbers and characteristics of the nation's people and housing. It replaces the "long form" of the decennial census. Using the American Community Survey covers the basics of how the ACS design and operations differ from the long-form sample; using the ACS for such applications as formula allocation of federal and state funds, transportation planning, and public information; and challenges in working with ACS estimates that cover periods of 12, 36, or 60 months depending on the population size of an area. This book also recommends priority areas for continued research and development by the U.S. Census Bureau to guide the evolution of the ACS, and provides detailed, comprehensive analysis and guidance for users in federal, state, and local government agencies, academia, and media.
Publisher:
ISBN:
Category : Reference
Languages : en
Pages : 360
Book Description
The American Community Survey (ACS) is a major new initiative from the U.S. Census Bureau designed to provide continuously updated information on the numbers and characteristics of the nation's people and housing. It replaces the "long form" of the decennial census. Using the American Community Survey covers the basics of how the ACS design and operations differ from the long-form sample; using the ACS for such applications as formula allocation of federal and state funds, transportation planning, and public information; and challenges in working with ACS estimates that cover periods of 12, 36, or 60 months depending on the population size of an area. This book also recommends priority areas for continued research and development by the U.S. Census Bureau to guide the evolution of the ACS, and provides detailed, comprehensive analysis and guidance for users in federal, state, and local government agencies, academia, and media.
Using Science to Improve the BLM Wild Horse and Burro Program
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309264944
Category : Technology & Engineering
Languages : en
Pages : 399
Book Description
Using Science to Improve the BLM Wild Horse and Burro Program: A Way Forward reviews the science that underpins the Bureau of Land Management's oversight of free-ranging horses and burros on federal public lands in the western United States, concluding that constructive changes could be implemented. The Wild Horse and Burro Program has not used scientifically rigorous methods to estimate the population sizes of horses and burros, to model the effects of management actions on the animals, or to assess the availability and use of forage on rangelands. Evidence suggests that horse populations are growing by 15 to 20 percent each year, a level that is unsustainable for maintaining healthy horse populations as well as healthy ecosystems. Promising fertility-control methods are available to help limit this population growth, however. In addition, science-based methods exist for improving population estimates, predicting the effects of management practices in order to maintain genetically diverse, healthy populations, and estimating the productivity of rangelands. Greater transparency in how science-based methods are used to inform management decisions may help increase public confidence in the Wild Horse and Burro Program.
Publisher: National Academies Press
ISBN: 0309264944
Category : Technology & Engineering
Languages : en
Pages : 399
Book Description
Using Science to Improve the BLM Wild Horse and Burro Program: A Way Forward reviews the science that underpins the Bureau of Land Management's oversight of free-ranging horses and burros on federal public lands in the western United States, concluding that constructive changes could be implemented. The Wild Horse and Burro Program has not used scientifically rigorous methods to estimate the population sizes of horses and burros, to model the effects of management actions on the animals, or to assess the availability and use of forage on rangelands. Evidence suggests that horse populations are growing by 15 to 20 percent each year, a level that is unsustainable for maintaining healthy horse populations as well as healthy ecosystems. Promising fertility-control methods are available to help limit this population growth, however. In addition, science-based methods exist for improving population estimates, predicting the effects of management practices in order to maintain genetically diverse, healthy populations, and estimating the productivity of rangelands. Greater transparency in how science-based methods are used to inform management decisions may help increase public confidence in the Wild Horse and Burro Program.