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ONLINE COURSE – Missing Data Analytics (MDAR01)

8th September 2021 - 10th September 2021

ONLINE COURSE – Missing Data Analytics (MDAR01)

Event Date

September, January 8th, 2021

Course Format

This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.

Course Program

TIME ZONE – GMT+1 – however all sessions will be recorded and made available allowing attendees from different time zones to follow.

Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.

Course Details

This course will cover introductory modelling for the analysis of missing data. Missing data is extremely common in all areas of science so this course will be of use to a wide variety of practitioners. The methods are presented both at a theoretical level and also with practical examples where all code is available. The practical classes include instructions on how to use the popular mice package.

The course is structured over 3 days and includes classes on:

  • An introduction to missing data analysis terminology, missing completely at random, missing at random, not missing at random
  • A revision of likelihood and regression approaches
  • The Fully Conditional Specification (FCS) approach
  • An introduction to the mice package
  • The use of Bayesian and likelihood-based methods in missing data analysis
  • Bayesian missing data analysis using JAGS
  • More advanced missing data analysis including non-ignorable and not missing at random methods
Intended Audiences

Research postgraduates, practicing academics, or other professionals from any field who would like to learn about missing data analysis and how it can help them produce better quality information from their data.

Venue

Delivered remotely

Course Information

Venue – Delivered remotely

Time zone – Western European Time

Availability – 30 places

Duration – 4 days

Contact hours – Approx. 28 hours

ECT’s – Equal to 3 ECT’s

Language – English

Teaching Format
A mixture of lectures and hands-on practicals. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
Assumed quantitative knowledge

A basic understanding of regression methods and generalised linear models.

Assumed computer background

Some familiarity with R including the ability to import/export data, manipulate data frames, fit basic statistical models, and generate simple exploratory and diagnostic plots.

Equipment and software requirements

Attendees will need to install/update R/RStudio and various additional R packages.

This can be done on Macs, Windows, and Linux.

R – https://cran.r-project.org/

RStudio – https://www.rstudio.com/products/rstudio/download/

PLEASE READ – CANCELLATION POLICY

Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.

If you are unsure about course suitability, please get in touch by email to find out more

info@clovertraining.co.uk

COURSE PROGRAMME

Wednesday 8th
Classes from 09:30 to 17:30
How to run a missing data analysis in mice
Introduction to Bayesian analysis and missing data
The use of Bayesian and likelihood-based methods in missing data analysis
The fully conditional specification approach to missing data analysis
Thursday 9th

Classes from 09:30 to 17:30
Including missing data in JAGS and Stan
An introduction to the mice package
Bayesian software tools JAGS/Stan for missing data analysis

Friday 10th

Classes from 09:30 to 17:30
Advanced missing data analysis methods
More advanced missing data analysis including non-ignorable and not missing at random methods
Missing data analysis in machine learning

Course Instructor

 

Prof. Andrew Parnell

Coming Soon

Details

Start:
8th September 2021
End:
10th September 2021
Event Category:

Venue

Delivered remotely (Ireland)
Western European Time, Ireland + Google Map