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This book serves as a hands-on guide to the "acs" R package for demographers, planners, and other researchers who work with American Community Survey (ACS) data. It gathers the most common problems associated with using ACS data and implements functions as a package in the R statistical programming language. The package defines a new "acs" class object (containing estimates, standard errors, and metadata for tables from the ACS) with methods to deal appropriately with common tasks (e.g., creating and combining subgroups or geographies, automatic fetching of data via the Census API, mathematical operations on estimates, tests of significance, plots of confidence intervals).
Book Synopsis Working with the American Community Survey in R by : Ezra Haber Glenn
Download or read book Working with the American Community Survey in R written by Ezra Haber Glenn and published by Springer. This book was released on 2016-10-06 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a hands-on guide to the "acs" R package for demographers, planners, and other researchers who work with American Community Survey (ACS) data. It gathers the most common problems associated with using ACS data and implements functions as a package in the R statistical programming language. The package defines a new "acs" class object (containing estimates, standard errors, and metadata for tables from the ACS) with methods to deal appropriately with common tasks (e.g., creating and combining subgroups or geographies, automatic fetching of data via the Census API, mathematical operations on estimates, tests of significance, plots of confidence intervals).
Download or read book The American Community Survey written by and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Over the past decade, the U.S. Census Bureau has implemented the American Community Survey as a replacement for its traditional decennial “long-form” survey. This year -- for the first time ever -- ACS data was made available at the census tract and block group level for the entire nation, representing geographies small enough to be useful to local planners; in the future these estimates will be updated on a yearly basis, providing much more current data than was ever available in the past. Although the ACS represents a bold strategy with great promise for planners working at the neighborhood scale, it will require them to become comfortable with statistical techniques and concerns that they have traditionally been able to avoid.To help with this challenge the author has been working with local-level planners to determine the most common problems associated with using ACS data, and has implemented these functions as a package in the R statistical programming language. The e ort is still in a “beta” stage, with much work to be done, but the basic framework is in place. The package defines a new “acs” class object (containing estimates, standard errors, and metadata for tables from the ACS), with methods to deal appropriately with common tasks (e.g., combining subgroups or geographies, mathematical operations on estimates, tests of significance, plots of confidence intervals, etc.).
Book Synopsis ACS.R by : Ezra Haber Glenn
Download or read book ACS.R written by Ezra Haber Glenn and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, the U.S. Census Bureau has implemented the American Community Survey as a replacement for its traditional decennial “long-form” survey. This year -- for the first time ever -- ACS data was made available at the census tract and block group level for the entire nation, representing geographies small enough to be useful to local planners; in the future these estimates will be updated on a yearly basis, providing much more current data than was ever available in the past. Although the ACS represents a bold strategy with great promise for planners working at the neighborhood scale, it will require them to become comfortable with statistical techniques and concerns that they have traditionally been able to avoid.To help with this challenge the author has been working with local-level planners to determine the most common problems associated with using ACS data, and has implemented these functions as a package in the R statistical programming language. The e ort is still in a “beta” stage, with much work to be done, but the basic framework is in place. The package defines a new “acs” class object (containing estimates, standard errors, and metadata for tables from the ACS), with methods to deal appropriately with common tasks (e.g., combining subgroups or geographies, mathematical operations on estimates, tests of significance, plots of confidence intervals, etc.).
A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.
Book Synopsis Complex Surveys by : Thomas Lumley
Download or read book Complex Surveys written by Thomas Lumley and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.
Following several years of testing and evaluation, the American Community Survey (ACS) was launched in 2005 as a replacement for the census "long form," used to collect detailed social, economic, and housing data from a sample of the U.S. population as part of the decennial census. During the first year of the ACS implementation, the Census Bureau collected data only from households. In 2006 a sample of group quarters (GQs)-such as correctional facilities, nursing homes, and college dorms-was added to more closely mirror the design of the census long-form sample. The design of the ACS relies on monthly samples that are cumulated to produce multiyear estimates based on 1, 3, and 5 years of data. The data published by the Census Bureau for a geographic area depend on the area's size. The multiyear averaging approach enables the Census Bureau to produce estimates that are intended to be robust enough to release for small areas, such as the smallest governmental units and census block groups. However, the sparseness of the GQ representation in the monthly samples affects the quality of the estimates in many small areas that have large GQ populations relative to the total population. The Census Bureau asked the National Research Council to review and evaluate the statistical methods used for measuring the GQ population. This book presents recommendations addressing improvements in the sample design, sample allocation, weighting, and estimation procedures to assist the Census Bureau's work in the very near term, while further research is conducted to address the underlying question of the relative importance and costs of the GQ data collection in the context of the overall ACS design.
Book Synopsis Measuring the Group Quarters Population in the American Community Survey by : National Research Council
Download or read book Measuring the Group Quarters Population in the American Community Survey written by National Research Council and published by National Academies Press. This book was released on 2011-01-29 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following several years of testing and evaluation, the American Community Survey (ACS) was launched in 2005 as a replacement for the census "long form," used to collect detailed social, economic, and housing data from a sample of the U.S. population as part of the decennial census. During the first year of the ACS implementation, the Census Bureau collected data only from households. In 2006 a sample of group quarters (GQs)-such as correctional facilities, nursing homes, and college dorms-was added to more closely mirror the design of the census long-form sample. The design of the ACS relies on monthly samples that are cumulated to produce multiyear estimates based on 1, 3, and 5 years of data. The data published by the Census Bureau for a geographic area depend on the area's size. The multiyear averaging approach enables the Census Bureau to produce estimates that are intended to be robust enough to release for small areas, such as the smallest governmental units and census block groups. However, the sparseness of the GQ representation in the monthly samples affects the quality of the estimates in many small areas that have large GQ populations relative to the total population. The Census Bureau asked the National Research Council to review and evaluate the statistical methods used for measuring the GQ population. This book presents recommendations addressing improvements in the sample design, sample allocation, weighting, and estimation procedures to assist the Census Bureau's work in the very near term, while further research is conducted to address the underlying question of the relative importance and costs of the GQ data collection in the context of the overall ACS design.
This book paints a portrait of social life in America by providing an accessible discussion of empirical economics research on issues such as illegal immigration, health care and climate change. All the studies in this book use the same data source: individual responses to the American Community Survey (ACS), the nation's largest household survey. The author identifies studies that clearly illustrate core econometric methods (such as regression control and difference-in-differences), replicates key statistics from the studies, and helps the reader to carefully interpret the statistics. This book has a companion website with replication files in R and Stata format. The Appendix to this book contains a guide to using the free R software, downloading the ACS and other public-use microdata, and running the replication files, which assumes no background knowledge on the part of the reader beyond introductory statistics. By opening up the hood on how top scholars use core econometric methods to analyze large data sets, a motivated reader with a decent computer and Internet connection can use this book to learn not only how to replicate published research, but also to extend the analysis to create new knowledge about important social phenomena. A more casual reader can skip the online supplements and still gain data-driven insights into social and economic behavior. The book concludes by describing how careful empirical estimates can guide decision making, through cost-benefit analysis, to find public policies that lead to greater happiness while accounting for environmental, public health and other impacts. With its accessible discussion, glossary, detailed learning goals, end of chapter review questions and companion resources, this book is ideal for use as a supplementary volume in introductory econometrics or research methods courses.
Book Synopsis Data and the American Dream by : Matthew J. Holian
Download or read book Data and the American Dream written by Matthew J. Holian and published by Springer Nature. This book was released on 2021-04-29 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book paints a portrait of social life in America by providing an accessible discussion of empirical economics research on issues such as illegal immigration, health care and climate change. All the studies in this book use the same data source: individual responses to the American Community Survey (ACS), the nation's largest household survey. The author identifies studies that clearly illustrate core econometric methods (such as regression control and difference-in-differences), replicates key statistics from the studies, and helps the reader to carefully interpret the statistics. This book has a companion website with replication files in R and Stata format. The Appendix to this book contains a guide to using the free R software, downloading the ACS and other public-use microdata, and running the replication files, which assumes no background knowledge on the part of the reader beyond introductory statistics. By opening up the hood on how top scholars use core econometric methods to analyze large data sets, a motivated reader with a decent computer and Internet connection can use this book to learn not only how to replicate published research, but also to extend the analysis to create new knowledge about important social phenomena. A more casual reader can skip the online supplements and still gain data-driven insights into social and economic behavior. The book concludes by describing how careful empirical estimates can guide decision making, through cost-benefit analysis, to find public policies that lead to greater happiness while accounting for environmental, public health and other impacts. With its accessible discussion, glossary, detailed learning goals, end of chapter review questions and companion resources, this book is ideal for use as a supplementary volume in introductory econometrics or research methods courses.
In this book you will learn how to use R with the tidycensus and tidyverse packages to explore and visualize US Census data.tidycensus is an R package that allows users to interface with the US Census Bureau's decennial Census and five-year American Community APIs and return tidyverse-ready data frames, optionally with simple feature geometry included. tidycensus is designed to help R users get Census data that is pre-prepared for exploration within the tidyverse, and optionally spatially with the sf package.If your work involves the use of data from the US Census Bureau and would like to use R to explore, manipulate, and visualize these datasets, the tidycensus and tidyverse packages are great tools for accomplishing these tasks. Beyond this, the sf package now allows R users to work with spatial data in an integrated way with tidyverse tools, and updates to the tigris package provide access to Census boundary data as sf objects.This book will also allow the student to learn, in detail, the fundamentals of the R language and additionally master some of the most efficient libraries for data visualization in chart, graph, and map formats. The student will learn the language and applications through examples and practice. No prior programming skills are required.
Book Synopsis Exploring and Visualizing US Census Data with R by : Eric Pimpler
Download or read book Exploring and Visualizing US Census Data with R written by Eric Pimpler and published by . This book was released on 2019-10-25 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book you will learn how to use R with the tidycensus and tidyverse packages to explore and visualize US Census data.tidycensus is an R package that allows users to interface with the US Census Bureau's decennial Census and five-year American Community APIs and return tidyverse-ready data frames, optionally with simple feature geometry included. tidycensus is designed to help R users get Census data that is pre-prepared for exploration within the tidyverse, and optionally spatially with the sf package.If your work involves the use of data from the US Census Bureau and would like to use R to explore, manipulate, and visualize these datasets, the tidycensus and tidyverse packages are great tools for accomplishing these tasks. Beyond this, the sf package now allows R users to work with spatial data in an integrated way with tidyverse tools, and updates to the tigris package provide access to Census boundary data as sf objects.This book will also allow the student to learn, in detail, the fundamentals of the R language and additionally master some of the most efficient libraries for data visualization in chart, graph, and map formats. The student will learn the language and applications through examples and practice. No prior programming skills are required.
Book Synopsis The Current Population Survey by : United States. Bureau of the Census
Download or read book The Current Population Survey written by United States. Bureau of the Census and published by . This book was released on 1978 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Examines the different populations and settings that can make surveys hard to conduct and discusses methods to meet these challenges.
Book Synopsis Hard-to-Survey Populations by : Roger Tourangeau
Download or read book Hard-to-Survey Populations written by Roger Tourangeau and published by Cambridge University Press. This book was released on 2014-08-28 with total page 675 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines the different populations and settings that can make surveys hard to conduct and discusses methods to meet these challenges.
Census data are widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions. Until recently, projects using US Census data have required proficiency with multiple web interfaces and software platforms to prepare, map, and present data products. This book introduces readers to tools in the R programming language for accessing and analyzing Census data, helping analysts manage these types of projects in a single computing environment. Chapters in this book cover the following key topics: • Rapidly acquiring data from the decennial US Census and American Community Survey using R, then analyzing these datasets using tidyverse tools; • Visualizing US Census data with a wide range of methods including charts in ggplot2 as well as both static and interactive maps; • Using R as a geographic information system (GIS) to manage, analyze, and model spatial demographic data from the US Census; • Working with and modeling individual-level microdata from the American Community Survey’s PUMS datasets; • Applying these tools and workflows to the analysis of historical Census data, other US government datasets, and international Census data from countries like Canada, Brazil, Kenya, and Mexico. Kyle Walker is an associate professor of geography at Texas Christian University, director of TCU’s Center for Urban Studies, and a spatial data science consultant. His research focuses on demographic trends in the United States, demographic data visualization, and software tools for open spatial data science. He is the lead author of a number of R packages including tigris, tidycensus, and mapboxapi.
Book Synopsis Analyzing US Census Data by : Kyle Walker
Download or read book Analyzing US Census Data written by Kyle Walker and published by CRC Press. This book was released on 2023-02-09 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Census data are widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions. Until recently, projects using US Census data have required proficiency with multiple web interfaces and software platforms to prepare, map, and present data products. This book introduces readers to tools in the R programming language for accessing and analyzing Census data, helping analysts manage these types of projects in a single computing environment. Chapters in this book cover the following key topics: • Rapidly acquiring data from the decennial US Census and American Community Survey using R, then analyzing these datasets using tidyverse tools; • Visualizing US Census data with a wide range of methods including charts in ggplot2 as well as both static and interactive maps; • Using R as a geographic information system (GIS) to manage, analyze, and model spatial demographic data from the US Census; • Working with and modeling individual-level microdata from the American Community Survey’s PUMS datasets; • Applying these tools and workflows to the analysis of historical Census data, other US government datasets, and international Census data from countries like Canada, Brazil, Kenya, and Mexico. Kyle Walker is an associate professor of geography at Texas Christian University, director of TCU’s Center for Urban Studies, and a spatial data science consultant. His research focuses on demographic trends in the United States, demographic data visualization, and software tools for open spatial data science. He is the lead author of a number of R packages including tigris, tidycensus, and mapboxapi.
