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@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:
1) An introduction to missing data analysis terminology, missing completely at random, missing at random, not missing at random
2) A revision of likelihood and regression approaches
3) The Fully Conditional Specification (FCS) approach
4) An introduction to the mice package
5) The use of Bayesian and likelihood-based methods in missing data analysis
6) Bayesian missing data analysis using JAGS
7) 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
Upcoming courses
Missing Data Analytics (MDAR01)
www.prstatistics.com/course/online-course-missing-data-analytics-mdar01
8 September 2021 - 10 September 2021
Functional ecology from organism to ecosystem: theory and computation (FEER02)
www.prstatistics.com/course/functional-ecology-from-organism-to-ecosystem-theory-and-computation-feer02/
13 September 2021 - 17 September 2021
Meta-analysis in ecology, evolution and environmental sciences (METR02)
www.prstatistics.com/course/meta-analysis-in-ecology-evolution-and-environmental-sciences-metr02/
13 September 2021 - 17 September 2021
Species Distribution Modeling using R (SDMR04)
www.prstatistics.com/course/species-distribution-modeling-using-r-sdmr04/
21 September 2021 - 30 September 2021
Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03)
www.prstatistics.com/course/multivariate-analysis-of-ecological-communities-in-r-with-the-vegan-package-vgnr03/
4 October 2021 - 8 October
Introduction to Data Wrangling and Data Visualization using R (DWDV01)
www.prstatistics.com/course/introduction-to-data-wrangling-and-data-visualization-using-r-dwdv01/
4 October 2021 - 8 October 2021
Species distribution modelling with Bayesian statistics in R (SDMB03)
www.prstatistics.com/course/species-distribution-modelling-with-bayesian-statistics-in-r-sdmb03/
6 December 2021 - 10 December 2021
ONLINE COURSE – Missing Data Analytics (MDAR01) This course will be delivered live
https://www.prstatistics.com/course/online-course-missing-data-analytics-mdar01
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@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:
1) An introduction to missing data analysis terminology, missing completely at random, missing at random, not missing at random
2) A revision of likelihood and regression approaches
3) The Fully Conditional Specification (FCS) approach
4) An introduction to the mice package
5) The use of Bayesian and likelihood-based methods in missing data analysis
6) Bayesian missing data analysis using JAGS
7) 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
Upcoming courses
Missing Data Analytics (MDAR01)
www.prstatistics.com/course/online-course-missing-data-analytics-mdar01
8 September 2021 - 10 September 2021
Functional ecology from organism to ecosystem: theory and computation (FEER02)
www.prstatistics.com/course/functional-ecology-from-organism-to-ecosystem-theory-and-computation-feer02/
13 September 2021 - 17 September 2021
Meta-analysis in ecology, evolution and environmental sciences (METR02)
www.prstatistics.com/course/meta-analysis-in-ecology-evolution-and-environmental-sciences-metr02/
13 September 2021 - 17 September 2021
Species Distribution Modeling using R (SDMR04)
www.prstatistics.com/course/species-distribution-modeling-using-r-sdmr04/
21 September 2021 - 30 September 2021
Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03)
www.prstatistics.com/course/multivariate-analysis-of-ecological-communities-in-r-with-the-vegan-package-vgnr03/
4 October 2021 - 8 October
Introduction to Data Wrangling and Data Visualization using R (DWDV01)
www.prstatistics.com/course/introduction-to-data-wrangling-and-data-visualization-using-r-dwdv01/
4 October 2021 - 8 October 2021
Species distribution modelling with Bayesian statistics in R (SDMB03)
www.prstatistics.com/course/species-distribution-modelling-with-bayesian-statistics-in-r-sdmb03/
6 December 2021 - 10 December 2021
Bayesian Data Analysis (BADA01)
https://www.prstatistics.com/course/bayesian-data-analysis-bada01/
10th January 2022 - 14th January 2022
Stable Isotope Mixing Models using SIBER, SIAR, MixSIAR (SIMM08)
https://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm08/
1st February 2022 - 4th February 2022