Using R for biostatistics - MacFarland, Thomas W.; Springer; Yates, Thomas M. (2021)
This book introduces the open source R software language that can be implemented in biostatistics for data organization, statistical analysis, and graphical presentation. In the years since the authors' 2014 work
1 Introduction: Biostatistics and R
1.1 Purpose of this Text
1.2 Development of Biostatistics
1.3 Development of R
1.4 How R is Used in this Text
1.5 Import Data into R
1.6 Addendum1: Efficient Programming with R, Project Workflow, and Good Programming Practices (gpp)
1.7 Addendum2: Preview of Descriptive Statistics and Graphics Using R
1.8 Addendum3: R and Beautiful Graphics
1.9 Addendum4: Research Designs Used in Biostatistics
1.10 Prepare to Exit, Save, and Later Retrieve this R Session
1.11 External Data and/or Data Resources Used in this Lesson
2 Data Exploration, Descriptive Statistics, and Measures of Central Tendency
2.1 Background
2.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions
2.3 Organize the Data and Display the Code Book
2.4 Conduct a Visual Data Check Using Graphics (e.g., Figures)
2.5 Descriptive Statistics for Initial Analysis of the Data
2.6 Quality Assurance, Data Distribution, and Tests for Normality
2.7 Statistical Test(s)
2.8 Summary
2.9 Addendum1: Specialized External Packages and Functions
2.10 Addendum2: Parametric v Nonparametric
2.11 Addendum3: Additional Practice Datasets for Data with Normal Distribution Patterns and Data That Do Not Exhibit Normal Distribution Patterns
2.12 Prepare to Exit, Save, and Later Retrieve this R Session
2.13 External Data and/or Data Resources Used in this Lesson
3 Student's t-Test for Independent Samples
3.1 Background
3.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions
3.3 Organize the Data and Display the Code Book
3.4 Conduct a Visual Data Check Using Graphics (e.g., Figures)
3.5 Descriptive Statistics for Initial Analysis of the Data
3.6 Quality Assurance, Data Distribution, and Tests for Normality
3.7 Statistical Test(s)
3.8 Summary of Outcomes
3.9 Addendum1: t-Statistic v z-Statistic
3.10 Addendum2: Parametric v Nonparametric
3.11 Addendum3: Additional Practice Datasets for Data with Normal Distribution Patterns and Data That Do Not Exhibit Normal Distribution Patterns
3.12 Prepare to Exit, Save, and Later Retrieve This R Session
3.13 External Data and/or Data Resources Used in this Lesson
4 Student's t-Test for Matched Pairs
4.1 Background
4.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions
4.3 Organize the Data and Display the Code Book
4.4 Conduct a Visual Data Check Using Graphics(e.g., Figures)
4.5 Descriptive Statistics for Initial Analysis of the Data
4.6 Quality Assurance, Data Distribution, and Tests for Normality
4.7 Statistical Test(s)
4.8 Summary of Outcomes
4.9 Addendum1: R-Based Tools for Unstacked (e.g. Wide) Data
4.10 Addendum2: Stacked Data and Student's t-Test for Matched Pairs
4.11 Addendum 3: The Impact of N on Student's t-Test
4.12 Addendum 4: Parametric v Nonparametric
4.13 Addendum5: Additional Practice Datasets for Data with Normal Distribution Patterns and Data That Do Not Exhibit Normal Distribution Patterns
4.14 Prepare to Exit, Save, and Later Retrieve This R Session
4.15 External Data and/or Data Resources Used in this Lesson
5 Oneway Analysis of Variance (ANOVA)
5.1 Background
5.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions
5.3 Organize the Data and Display the Code Book
5.4 Conduct a Visual Data Check Using Graphics(e.g., Figures)
5.5 Descriptive Statistics for Initial Analysis of the Data
5.6 Quality Assurance, Data Distribution, and Tests for Normality
5.7 Statistical Test(s)
5.8 Summary of Outcomes
5.9 Addendum1: Other Packages for Display of Oneway ANOVA
5.10 Addendum2: Parametric v Nonparametric
5.11 Addendum3: Additional Practice Data Sets
5.12 Prepare to Exit, Save, and Later Retrieve This R Session
5.13 External Data and/or Data Resources Used in this Lesson
6 Twoway Analysis of Variance (ANOVA)
6.1 Background
6.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions
6.3 Organize the Data and Display the Code Book
6.4 Conduct a Visual Data Check Using Graphics (e.g., Figures)
6.5 Descriptive Statistics for Initial Analysis of the Data
6.6 Quality Assurance, Data Distribution, and Tests for Normality
6.7 Statistical Test(s)
6.8 Summary of Outcomes
6.9 Addendum 1: Other Packages for Display of Twoway ANOVA
6.10 Addendum 2: Parametric v Nonparametric
6.11 Addendum 3: Additional Practice Data Sets
6.12 Prepare to Exit, Save, and Later Retrieve This R Session
6.13 External Data and/or Data Resources Used in this Lesson
7 Correlation, Association, Regression, Likelihood, and Prediction
7.1 Background
7.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions
7.3 Organize the Data and Display the Code Book
7.4 Quality Assurance, Data Distribution, and Tests for Normality
7.5 Statistical Test(s)
7.6 Summary of Outcomes
7.7 Addendum 1: Multiple Regression
7.8 Addendum 2: Likelihood and Odds Ratio
7.9 Addendum 3:Parametric v Nonparametric
7.10 Addendum 4: Additional Practice Data Sets
7.11 Prepare to Exit, Save, and Later Retrieve This R Session
7.12 External Data and/or Data Resources Used in this Lesson
8 Working with Large and Complex Datasets
8.1 Background
8.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions
8.3 Organize the Data and Display the Code Book
8.4 Conduct a Visual Data Check Using Graphics (e.g., Figures)
8.5 Descriptive Statistics for Initial Analysis of the Data
8.6 Quality Assurance, Data Distribution, and Tests for Normality
8.7 Statistical Test(s)
8.8 Summary of Outcomes
8.9 Addendum1: Additional Graphics, to Show Relationships Between and Among Data
8.10 Addendum2: Graphics Using the lattice Package
8.11 Addendum3: Graphics Using the ggplot2 Package
8.12 Addendum 4: Beyond an Introduction to R
Use the tidyverse to Create Subsets of Original Datasets
8.13 Prepare to Exit, Save, and Later Retrieve This R Session
8.14 External Data and/or Data Resources Used in this Lesson
9 Future Actions and Next Steps
9.1 Use of This Text
9.2 R and Beautiful Reporting with R Markdown
9.3 Future Use of R for Biostatistics
9.4 Big Data and Bio Informatics
9.5 External Resources
9.6 Contact the Authors.
Includes Index
Keywords: Agriculture -- Biometry -- Biometry Data processing -- Biostatistics -- Public Health -- R (Computer program language) -- Software -- Statistical Theory and Methods -- Statistics for Life Sciences, Medicine, Health Sciences