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ONLINE COURSE – Missing Data Analytics (MDAR01) This course will be delivered live
30 September 2020 - 2 October 2020£425.00
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak.
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.
TIME ZONE – Western European Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email email@example.com for full details or to discuss how we can accommodate you).
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
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
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
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 firstname.lastname@example.org. 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.
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
A laptop/personal computer with a working version or R and RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK email@example.com
Wednesday 30th – Classes from 09:30 to 17:30
Thursday 1st – Classes from 09:30 to 17:30
Friday 2nd – Classes from 09:30 to 17:30