Visualizing Surveys In R
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Visualizing Surveys in R
Visualizing Surveys in R is about creating static, print quality figures from survey data using R. The focus is not, for example, on statistical analysis of survey data, but rather on giving concrete solutions for typical problems in visualizing survey data. While there are many excellent books on data visualization, surveys and R, the aim of this book is to bring these topics together, and offer practical instructions for visualizing surveys in R. Features Introduction to survey data: variables, categories, and scales Description of a process for visualizing survey data Recommendations for reading survey data into R Advice on building a survey dataset in R to facilitate versatile plotting Step-by-step recipes in R for creating useful plots from survey data The book is intended for researchers who regularly use surveys and are interested in learning how to seize the vast possibilities and the flexibility of R in survey analysis and visualizations. The book is also valuable for psychologists, marketeers, HR personnel, managers, and other professionals who wish to standardize and automate the process for visualizing survey data. Finally, the book is suitable as a course textbook, either more widely on survey studies, or more strictly on visualizing survey data in R.
Interactive visualization to facilitate monitoring longitudinal survey data and paradata
Surveys often require monitoring during data collection to ensure progress in meeting goals or to evaluate the interim results of an embedded experiment. Under complex designs, the amount of data available to monitor may be overwhelming and the production of reports and charts can be costly and time consuming. This is especially true in the case of longitudinal surveys, where data may originate from multiple waves. Other such complex scenarios include adaptive and responsive designs, which were developed to act on the results of such monitoring to implement prespecified options or alternatives in protocols. This paper discusses the development of an interactive web-based data visualization tool, the Adaptive Total Design (ATD) Dashboard, which we designed to provide a wide array of survey staff with the information needed to monitor data collection daily. The dashboard was built using the R programming language and Shiny framework and provides users with a wide range of functionality to quickly assess trends. We present the structure of the data used to populate the dashboard, its design, and the process for hosting it on the web. Furthermore, we provide guidance on graphic design, data taxonomy, and software decisions that can help guide others in the process of developing their own data collection monitoring systems. To illustrate the benefits of the dashboard, we present examples from the National Longitudinal Study of Adolescent to Adult Health (Add Health). We also discuss features of the dashboard to be developed for future waves of Add Health.
Exploring Complex Survey Data Analysis Using R
Surveys are powerful tools for gathering information, uncovering insights, and facilitating decision-making. However, to ensure the accurate interpretation of results, they require specific analysis methods. In this book, readers embark on an in-depth journey into conducting complex survey analysis with the {srvyr} package and tidyverse family of functions from the R programming language. Intended for intermediate R users familiar with the basics of the tidyverse, this book gives readers a deeper understanding of applying appropriate survey analysis techniques using {srvyr}, {survey}, and other related packages. With practical walkthroughs featuring real-world datasets, such as the American National Election Studies and Residential Energy Consumption Survey, readers will develop the skills necessary to perform impactful survey analysis on survey data collected through a randomized sample design. Additionally, this book teaches readers how to interpret and communicate results of survey data effectively. Key Features: Uses the {srvyr} package and tidyverse family of packages. Grants a conceptual understanding of the statistical methods that the functions apply to. Includes practical walkthroughs using publicly available survey data. Provides the reader with the tools for interpreting, visualizing, and presenting results.