2018 Spring R Course Series

2018 Spring R Course Series

 

R software logo

R is a powerful and flexible software environment for statistical analysis and graphics. R is freely available, facilitating analysis and model transparency and reproducibility. Over recent years, it has become increasingly popular among health researchers. 

Participant experience

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

For Registration Form scroll below.


Courses:

 

Introduction to R for health researchers

Monday, February 26, 2018, 9 am — 4 pm Basic use of R and R Studio

 

Introduction to R for regression analysis

Monday, April 16, 2018, 9 am — 4 pm Models for continuous, binary and count data

 

Introduction to R for survival analysis

Wednesday, May 23, 2018, 9 am — 4 pm Handling time-to-event data

 

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. 

Ella Huszti , MSc, PhD, Senior Biostatistician at Biostatistics Research Unit (BRU) at University Health Network, Toronto.

John Matelski, MSc, Biostatistician at the Biostatistics Research Unit, University Health Network, Toronto.

Jin Ma, MSc, PhD, 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.

 


 

Fees, Registration, Contact Information & Location Details

 

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 24, 200 Elizabeth Street, Toronto, ON M5G 2C4

 

Single session:

$ 200 (includes lunch & snacks)

Multiple sessions discount:

$300 for 2 sessions

$450 for all 3 sessions

 

Registration

Complete the Registration Form . After submission, you will proceed to payment page.

 

For more information contact:

email: beena.vyas@thebru.ca

 

UHN & THETA location map

 

 

 

 

 

 

 

 


 

Introduction to R for Health Researchers

 

Monday February 26, 2018, 9 am — 4 pm

 

Primary Instructor: George Tomlinson, PhD

Secondary Instructor: John Matelski, MSc

 

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
George Tomlinson photo

 

 

 

 

 

 

 

 

 

 

 

 

 


 

Introduction to R for Regression Analysis

 

Monday, April 16, 2018, 9 am — 4 pm

 

Primary Instructor: Nicholas Mitsakakis, PhD

Secondary Instructor: John Matelski, MSc

 

How to run widely-used regression models for three types of outcomes

  • continuous
  • binary
  • count

How to output and obtain the key results

  • parameter estimates
  • confidence intervals for parameters
  • global measures of model fit
  • p-values

How to assess quality of the model fit

  • diagnostics plots
  • goodness of fit statistics

How to compare different models

  • nested models
  • non-nested models

How to obtain predictions from a fitted model

How to validate a model using the bootstrap

Nicholas Mitsakakis photo

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


 

Introduction to R for Survival Analysis

 

Wednesday May 23, 2018, 9 am — 4 pm

 

Primary Instructor: Ella Huszti, PhD

Secondary Instructor: Leah Szadkowski, MSc

 

Basic Concepts

  • Censoring
  • Survival function
  • Hazard function

Descriptive analyses

  • Kaplan-Meier Curves
  • Survival estimates

Proportional Hazards Model

  • Data preparation
  • Checking the proportional hazards assumption 
  • Cox proportional hazards model

Time Dependent Covariates

  • Concepts
  • Preparing data with a time dependent covariate
  • Using a time dependent covariate in a Cox proportional hazards model

Competing Risks Models

  • Concepts
  • Modeling the cause-specific hazard of the outcome
  • Modeling the cumulative incidence function (i.e., Fine & Gray models)
Ella Huszti photo