Introduction to Small Area Estimation Techniques : A Practical Guide for National Statistics Offices.

Cover -- Title -- Copyright -- Contents -- Tables, Figures, and Boxes -- Foreword -- Acknowledgments -- Abbreviations -- Chapter I: Introduction -- 1.1. What is Small Area Estimation and Why Do We Need It? -- Chapter II: Developing a Small Area Estimation Plan -- 2.1 Goal or Purpose of Small Area Estimation -- 2.2 Variable of Interest -- 2.3 Level of Disaggregation and Data Requirements -- 2.4 Approach to Small Area Estimation and Choosing a Specific Technique or Model -- 2.5 Quality Assessment of the Small Area Estimates -- 2.6 Dissemination Strategy for Presentation of the Small Area Estimates -- Chapter III: Data Management Using R -- 3.1 Overview of R and RStudio -- 3.2 Fundamentals of R -- 3.3 Data Manipulation Using dplyr and tidyr -- 3.4 Linear Regression in R -- 3.5 R Packages for Small Area Estimation -- Chapter IV: Approaches in Small Area Estimation -- 4.1 Direct Survey Estimation -- 4.2 Small Area Estimation Using Auxiliary Information -- 4.3 Small Area Estimation Using Regression-Based Models -- Chapter V: Visualizing Small Area Estimates Using R -- Chapter VI: Conclusion -- Appendixes -- 1. Description of R Packages Identified and Used in the Illustrations -- 2. Data Files Identified and Used in the Illustrations -- 3. Model Building -- References.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.