This book provides a complete practical guide of processing data in public health with R language. On the basis of the author’s research and teaching experiences, this book serves either as a textbook for undergraduates and graduates in public health or as a tutorial for self-learning. Many first-hand examples are presented with source data, R scripts, and graphs, as well as detailed explanations, which could be easily reproduced by readers so as to better understand the data processing principles and procedures. Popular and novel R packages in public health are introduced as well.
Author(s): Peng Zhao
Publisher: Springer
Year: 2023
Language: English
Pages: 200
City: Singapore
Preface
Contents
List of Figures
List of Tables
1 Preparing Tools
1.1 Chapter Highlights
1.2 Tools
1.3 Set Up R
1.3.1 R
1.3.2 RStudio
1.4 Programming Basics
1.5 R Packages
1.5.1 Installation
1.5.2 Packages in Public Health
1.5.3 Datasets in Packages
1.6 R Help
1.6.1 Built-in Documents
1.6.2 Examples and Demonstrations
1.6.3 Asking Questions
1.7 Base R, data.table, and tidyverse
1.8 Exercises
References
2 Planning Data
2.1 Chapter Highlights
2.2 Research Design
2.3 Literature Review
2.3.1 Relevant R Packages
2.3.2 The bibliometrix Package
2.3.3 The scholar Package
2.4 Establish a Data Plan
2.4.1 Workflow
2.4.2 Mind Maps
2.4.3 Gannt Charts
2.5 Exercises
References
3 Collecting Data
3.1 Chapter Highlights
3.2 Sampling Data
3.2.1 Probability Sampling
3.2.2 Non-probability Sampling
3.3 Recording Data
3.3.1 Surveys and Questionnaires
3.3.2 Desktop Questionnaire Platform
3.3.3 Online Questionnaire Platform
3.3.4 Databases and Tables
3.3.5 Using Secondary Data
3.4 Exercises
References
4 Importing and Exporting Data
4.1 Chapter Highlights
4.2 Import Data Manually
4.3 Using RStudio Dialogues
4.4 Comma/Tab Separated Values
4.5 Default Formats in R
4.6 Other Software Dependent Data Files
4.7 Online Sources
4.8 Data Shipped with R Packages
4.9 Exercises
References
5 Cleaning Data
5.1 Chapter Highlights
5.2 Introduction
5.3 File Information
5.4 Dimensions and Structure
5.5 Mislabelled Variables
5.6 Incorrect Data Types
5.7 Text Inconsistencies
5.8 Anomalies
5.9 Missing Values
5.10 Other Operations
5.11 Exercises
References
6 Describing Data
6.1 Chapter Highlights
6.2 Categorical Data
6.2.1 Contingency Tables
6.2.2 Marginal Statistics
6.3 Numerical Data
6.3.1 Central Tendency
6.3.2 Spread
6.3.3 Distribution Shape
6.3.4 Extended Summaries
6.4 Grouped Summary
6.5 Visualization
6.6 Exercise
References
7 Analyzing Data
7.1 Chapter Highlights
7.2 Probability Distribution Functions in R
7.3 Hypothesis Tests
7.3.1 R Functions and Common Steps
7.3.2 Student's t-Test
7.3.3 \chi ^2-test
7.3.4 Analysis of Variance (ANOVA)
7.4 Regressions
7.4.1 Common Regression Models
7.4.2 Linear Regression Model
7.4.3 Logistic Regression Model
7.4.4 Cox Regression Model
7.5 Exercises
References
8 Visualizing Data
8.1 Chapter Highlights
8.2 Introduction
8.3 Plotting Systems in R
8.3.1 Base R
8.3.2 ggplot2
8.3.3 plotly
8.3.4 Other Systems
8.4 Pie Charts
8.5 Bar Charts
8.5.1 For One-Way Frequency Tables
8.5.2 For Two-Way Contingency Tables
8.5.3 For Multiple-Way Tables
8.6 Dot Charts and Strip Charts
8.7 Histograms, Box Plots, and Violin Charts
8.8 Scatterplots
8.8.1 For Two Variables
8.8.2 For Pairwise Variables
8.8.3 For Multiple Variables
8.8.4 Line Charts and Area Charts
8.9 Export Graphs
8.10 Exercises
References
9 Presenting Data
9.1 Chapter Highlights
9.2 Channels
9.3 General Principles
9.4 R Markdown
9.4.1 Set Up R Markdown
9.4.2 Structure of an R Markdown Document
9.5 Presenting Data via Statements
9.5.1 Summaries
9.5.2 Hypothesis Tests
9.5.3 Regressions
9.6 Presenting Data via Tables
9.7 Presenting Data via Graphs
9.8 Integration of Statements, Tables, and Graphs
References
10 Managing Data
10.1 Chapter Highlights
10.2 Introduction
10.3 Data Management Framework
10.3.1 The prodigenr Package
10.3.2 The rosr Package
10.4 Raw Data
10.5 Metadata
10.5.1 Introduction
10.5.2 Metadata in Variable Names
10.5.3 Metadata in Labels
10.5.4 Metadata in Headers or Independent Files
10.5.5 Metadata in R Packages
10.6 Scripts
10.7 Version Control
10.8 Exercises
References
