Logistic Regression: an Introduction

University College London

Course

In London

£ 150 VAT inc.

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Description

  • Type

    Course

  • Level

    Intermediate

  • Location

    London

  • Class hours

    5h

  • Duration

    1 Day

  • Start date

    Different dates available

This one-day course focuses on understanding the principles of logistic regression using the notions of odds, odds ratios and transformations.
It includes discussion of how good the given model is, and ways of improving it.
This course is delivered by UCL's Centre for Applied Statistics Courses (CASC) - part of the UCL Great Ormond Street Institute of Child Health (ICH).

Facilities

Location

Start date

London
See map
Gower Street, WC1E 6BT

Start date

Different dates availableEnrolment now open

About this course

By the end of the course you should be able to:
understand when it is relevant to choose logistic regression
understand the use of odds, odds ratios and transformations in logistic regression
correctly interpret the results of logistic regression
choose the best logistic model that describes the relationship under question
understand how logistic regression can be extended for nominal and ordinal outcomes

You can request a certificate of attendance for this course once you've completed it.

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Reviews

This centre's achievements

2018

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 14 years

Subjects

  • Scientific
  • Analysed
  • Regression analysis
  • Analyse binary
  • Logistic
  • SPSS
  • Output
  • SPSS output
  • Odds ratios
  • Logistic Regression

Course programme

Binary (proportion/percentage) outcomes are common in medical and scientific research. However, such outcomes can't be validly analysed using basic linear regression analysis.

It's important to understand how to analyse binary outcomes appropriately to ensure you can draw useful and valid conclusions from the data.

The course covers the following key topics:

  • Odds ratios as a means of comparing binary outcomes between two groups
  • How logistic regression allows for other factors within this comparison
  • The basics of logistic regression
  • Model selection and goodness-of-fit with applied examples
  • Interpretation of SPSS output
  • Discussion of extension to the analysis of ordinal outcomes

See related categories

Logistic Regression: an Introduction

£ 150 VAT inc.

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