Training Calendar

An Introduction to Medical Statistics using Stata

Sofitel, Downtown Dubai 2 days (3rd December 2018 - 4th December 2018) Stata Introductory
Medical statistics, Statistics

This two day introductory statistics course is intended for people who are reasonably familiar with Stata (e.g. have attended the one-day introduction to Stata course) but who would like to develop their statistical analysis skills.

In this two-day course we will look at how to use Stata to analyse data that typically arises in medical research including continuous outcomes e.g. blood pressure, binary outcomes e.g. dead/alive and time-to-event outcomes e.g. time to myocardial infarction. We will look at how to fit appropriate models in Stata and how to interpret the resulting output. We will look at how to adjust for multiple explanatory variables, allow for interactions and how to obtain model predictions.

What topics will you cover?

  • Introduction to course and data
  • Principles of statistical analysis
  • For each of continuous, binary and time-to-event outcomes:
    • Fitting models in Stata and understanding the output
    • Including categorical explanatory variables
    • Fitting multiple explanatory variables
    • Fitting interactions
    • Comparing models and model selection
    • Obtaining model predictions
  • Reporting results
    • For time-to-event outcomes:
    • Setting up survival data in Stata

An example study will be used throughout to help illustrate how to carry out a statistical analysis.

The examples used throughout will be from the field of medical statistics. However, the underlying principles will have application in many areas of research. Throughout the day we will emphasise good practice for carrying out and reporting statistical analysis. The format for the training will be a series of ‘from the front’ demonstrations, which participants will follow along on their own computers, interspersed with short exercises. A series of do-files will be built up over the two days which participants can take away along with the data as a record of what they have done.

Course Agenda

Day 1

Session 1: Linear Regression 1

  • Analysis of continuous outcome variables
  • Univariable linear regression
  • Fitting binary, categorical and continuous explanatory variables

Session 2: Linear Regression 2

  • Multivariable linear regression
  • Fitting quadratic and interaction terms
  • Comparing models using F-tests
  • Obtaining fitted values and model checking

Session 3: Logistic Regression 1

  • Analysis of binary outcomes
  • Univariable logistic regression
  • Fitting binary, categorical and continuous explanatory variables

Session 4: Logistic Regression 2

  • Multivariable logistic regression
  • Comparing models using likelihood ratio tests
  • Assessing model performance using area under the curve

Day 2

Session 1: Survival Analysis 1

  • Introduction to analysis of time-to-event outcomes
  • Setting up data for survival analysis
  • Commands for summarising survival data

Session 2: Survival Analysis 2

  • Producing Kaplan-Meier curves
  • Univariable Cox proportional hazards modelling
  • Fitting binary, categorical and continuous explanatory variables

Session 3: Survival Analysis 3

  • Multivariable Cox proportional hazards modelling
  • Comparing models using likelihood ratio tests
  • Testing the proportional hazards assumption

Session 4: Q&A session

Learning Ratio: Theory 20% Demonstration 30% Practical 50%

Principal texts for pre-course reading

  • An Introduction to Stata for Health Researchers - Svend Juul
  • A Handbook of Statistical Analysis Using Stata 4th edition - Sophia Rabe-Hesketh and Brian Everitt
  • Regression Methods in Biostatistics – Linear, Logisitic, Survival and Repeated Measures Models–Eric Vittinghoff, David Glidden, Stephen Shiboski, Cahrles McCulloch, Springer

The following books are good general introductions to medical statistics but do not focus on any statistical software:

  • Essential Medical Statistics - B Kirkwood and J Sterne, 2nd Edition, Blackwell Science
  • Practical Statistics for Medical Research – Doug Altman, Chapman & Hall/CRC

Prerequisites

  • Familiarity with Stata is required. Basic knowledge of statistics and econometric concepts such as linear regression, logistic regression and survival analysis is advisable.
    • All costs exclude local taxes, where applicable.
    • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrollment).
    • Additional discounts are available for multiple registrations.
    • Cost includes course materials, lunch and refreshments.
    • If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
    • Payment of course fees required prior to the course start date.
    • Registration closes 5-calendar days prior to the start of the course.
      • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
      • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
      • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

    The number of delegates is restricted. Please register early to guarantee your place.

    •  CommercialAcademicStudent
      2 Day Course (03/12/2018 - 04/12/2018)

    All prices exclude VAT or local taxes where applicable.

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