The BRU Spring and Summer 2019 R Course Series

Courses:

Introduction to R

(Nicholas Mitsakakis, George Tomlinson) (2 half days)

May 13, 2019, 9:00-12:30 and
May 14, 2019, 9:00-12:30

From Raw to Ready: Preparing Your Data in R

(Leah Szadkowski, Nicholas Mitsakakis)
June 3, 2019, 9:00-12:30

Data Visualization with ggplot2

(Juan Pablo Diaz Martinez, Julie Hudson)
June 26, 2019, 9:00-12:30

Reproducible Reports in R

(Leah Szadkowski, Juan Pablo Diaz Martinez)
July 8, 2019, 9:00-12:30

Instructors:

George Tomlinson, MSc, PhD, Biostatistician, Director of the Biostatistics Research Unit, University Health Network, Toronto;  Associate Professor at the Institute of Health Policy, Management and Evaluation, University of Toronto. 

Nicholas Mitsakakis, MSc, PhD, Senior Biostatistician at Biostatistics Research Unit (BRU) at University Health Network,  Assistant Professor at the Institute of Health Policy, Management and Evaluation, University of Toronto. 

Juan Pablo Diaz Martinez, BSc, MSc, PhD (c), Biostatistician at the Biostatistics Research Unit, University Health Network, Toronto.

Leah Szadkowski, BSc, MSc, Biostatistician at Biostatistics Research Unit (BRU) at University Health Network, Toronto.

Julie Hudson, BSc, MSc, Biostatistician at the Biostatistics Research Unit, University Health Network, Toronto.

The course will be held at:

Toronto Health Economics and Technology Assessment (THETA) Collaborative University Health Network Toronto General Hospital Eaton Building, 10th Floor, Room 240, 200 Elizabeth Street, Toronto, ON M5G 2C4

Pricing:

Introduction to R (2 half days) $200

Other courses (half day) $100 each

Package: all 5 courses for $400

Registration

Complete the Registration Form.

For more information contact:

email: beena.vyas@thebru.ca

May 13, 2019, 9:00-12:30 and May 14, 2019, 9:00-12:30

Participant experience

Participants will be expected to have some basic knowledge of statistics but are not expected to be familiar with R. 

Primary Instructor: George Tomlinson, PhD

Secondary Instructor: Nicholas Mitsakakis, PhD

Getting to know R and R Studio

• The R Studio programming environment
• R script files
• Objects, assignment, and functions
• Vectors and data frames
• Reading in data and saving results

Basic R Graphics

• Boxplots
• Histograms
• Scatterplots
• Adding colours and informative labels to figures

Useful Statistical Tests and Procedures

• Categorical data: Binomial, Chi-squared, and Fisher’s Exact tests
• Continuous data: t-test and non-parametric tests
• Sample size calculations

June 3, 2019, 9:00-12:30

Participant experience

Some exposure to R required.

Primary Instructor: Nicholas Mitsakakis, PhD

Secondary Instructor: Leah Szadkowski, MSc

Guidelines for raw data collection

• Describing raw data
• summary
• describe

Transforming datasets

• merge
• join_all
• dcast

Dates

• chron
• lubridate

Cleaning and deriving data

• apply family
• dplyr
• parse
• grepl

Summarizing data

• CreateTableOne

June 26, 2019, 9:00-12:30

Participant experience

Some exposure to R required.

Primary Instructor: Juan Pablo Diaz Martinez, BSc, MSc, PhD (c)

Secondary Instructor: Julie Hudson, BSc, MSc

Introduction

• Why ggplot2?
• Grammar of graphics

Geometric objects

• Points
• Histograms
• Boxplots
• Densities
• Others (polygons, dotplots, etc.)

Adjusting the plot

Best Practices of Data Visualization

• Scales
• Shapes and colours
• Axes
• Legends
• Positioning

  Other features

  • Faceting
  • Themes
  • Model Visualization
• Dos and Don’ts
• Smart graphing elements
• Examples

July 8, 2019, 9:00-12:30

Participant experience

Some exposure to R required.

Primary Instructor: Juan Pablo Diaz Martinez, BSc, MSc, PhD (c)

Secondary Instructor: Leah Szadkowski, BSc, MSc

Why make reproducible reports?

R markdown, the basics

• Word, PDF, HTML
• LaTeX
• Code Chunks
• Adding and formatting text

Tables

References

• knitr
• pander
• kable
• excel output

  Figures

  • sizing
  • ggsave
  • ggarrange
• Cross-references
• Bibliographies and citations