[R-sig-eco] Missing Data Analytics (MDAR01)

[Oliver Hooker]

ONLINE COURSE – Missing Data Analytics (MDAR01) This course will be
delivered live

https://www.prstatistics.com/course/online-course-missing-data-analytics-mdar01-this-course-will-be-delivered-live/

Email oliverhooker using prstatistics.com

8 September 2021 - 10 September 2021

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
oliverhooker using prstatistics.com for full details or to discuss how we
can accommodate you).

Course overview:
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

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


-- 
Oliver Hooker PhD.
PR statistics

2020 publications;
Parallelism in eco-morphology and gene expression despite variable
evolutionary and genomic backgrounds in a Holarctic fish. PLOS
GENETICS (2020). IN PRESS

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