[R-sig-ME] Introduction to Bayesian hierarchical modelling using R (IBHM04)

[Oliver Hooker]

Introduction to Bayesian hierarchical modelling using R (IBHM04)

https://www.psstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm04/

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This course will be delivered by Dr Andrew Parnell form the 23rd -
27th March in Glasgow City Centre.

Course Overview:
This course will cover introductory hierarchical modelling for
real-world data sets from a Bayesian perspective. These methods lie at
the forefront of statistics research and are a vital tool in the
scientist’s toolbox. The course focuses on introducing concepts and
demonstrating good practice in hierarchical models. All methods are
demonstrated with data sets which participants can run themselves.
Participants will be taught how to fit hierarchical models using the
Bayesian modelling software Jags and Stan through the R software
interface. The course covers the full gamut from simple regression
models through to full generalised multivariate hierarchical
structures. A Bayesian approach is taken throughout, meaning that
participants can include all available information in their models and
estimates all unknown quantities with uncertainty. Participants are
encouraged to bring their own data sets for discussion with the course
tutors.

Monday 8th – Classes from 09:00 to 17:00

Module 1: Introduction to Bayesian Statistics
Module 2: Linear and generalised linear models (GLMs)
Practical: Using R, Jags and Stan for fitting GLMs
Round table discussion: Understanding Bayesian models

Tuesday 9th – Classes from 09:00 to 17:00

Module 3: Simple hierarchical regression models
Module 4: Hierarchical models for non-Gaussian data
Practical: Fitting hierarchical models
Round table discussion: Interpreting hierarchical model output

Wednesday 10th – Classes from 09:00 to 17:00

Module 5: Hierarchical models vs mixed effects models
Module 6:  Multivariate and multi-layer hierarchical models
Practical: Advanced examples of hierarchical models
Round table discussion: Issues of continuous vs discrete time

Thursday 11th – Classes from 09:00 to 16:00

Module 7: Shrinkage and variable selection
Module 8: Hierarchical models and partial pooling
Practical: Shrinkage modelling
Round table discussion Bring your own data set

Friday 12th – Classes from 09:00 to 16:00

Final day for recap session, catch up time and bring your own data set


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1. March 23rd – 27th
INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING USING R (IBHM04)
Glasgow, Scotland, Dr Andrew Parnell
https://www.psstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm04/

2. March 30th – April 3rd
INTRODUCTION TO STATISTICAL MODELLING FOR PSYCHOLOGISTS IN R (IPSY03)
Glasgow, Scotland, Dr Dale Barr
https://www.psstatistics.com/course/introduction-to-statistics-using-r-for-psychologists-ipsy03/

3. May 4th – May 8th
PYTHON FOR DATA SCIENCE, MACHINE LEARNING, AND SCIENTIFIC COMPUTING (PDMS02)
Glasgow, Scotland, Dr. Mark Andrews
https://www.prinformatics.com/course/python-for-data-science-machine-learning-and-scientific-computing-pdms02/

4. May 11th – 15th
BIOINFORMATICS WITH LINUX WITH PYTHON (BILP01)
Glasgow, Scotland, Dr. Martin Jones
https://www.prinformatics.com/course/introduction-to-linux-workflows-for-biologists-ibul04/

5. May 11th – 15th
FORMALIZING UNCERTAINTY: FUZZY LOGIC IN SPECIES DISTRIBUTION AND
DIVERSITY PATTERNS (FLDM01)
Glasgow, Scotland, Dr. Marcia Barbosa
https://www.prstatistics.com/course/formalizing-uncertainty-fuzzy-logic-in-species-distribution-and-diversity-patterns-fldm01/

6. May 18th – 22nd
STRUCTUAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (SEMR02)
Glasgow, Scotland, Dr. Jonathan Lefcheck, Dr. Jim (ames) Grace
https://www.prstatistics.com/course/structural-equation-modelling-for-ecologists-and-evolutionary-biologists-semr02/

7. May 25th – 29th
GENERALISED LINEAR (MIXED) (GLMM), NONLINEAR (NLGLM) AND GENERAL
ADDITIVE MODELS (MIXED) (GAMM) (GNAM01)
Glasgow, Scotland, Dr Mark Andrews
https://www.psstatistics.com/course/generalised-linear-glm-nonlinear-nlglm-and-general-additive-models-gam-gnam02/

8. June 1st – 5th
LANDSCAPE GENETIC DATA ANALYSIS USING R (LNDG03)
Glasgow, Scotland, Prof. Rodney Dyer
http://www.prstatistics.com/course/landscape-genetic-data-analysis-using-r-lndg04/

9. June 8th – 12th
STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR (SIMM06)
Glasgow, Scotland, Dr. Andrew Parnell, Dr. Andrew Jackson
www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm06/

10. June 17th – 21st
ADVANCED PYTHON FOR BIOLOGISTS (APYB04)
Glasgow, Scotland, Dr. Martin Jones
www.prinformatics.com/course/advanced-python-biologists-apyb04/

11. July 20th – 24th
APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (ABME06)
Glasgow, Scotland, Dr Matt Denwood
https://www.prstatistics.com/course/applied-bayesian-modelling-for-ecologists-and-epidemiologists-abme06/

12. July 27th – 31st
SPECIES DISTRIBUTION MODELLING (DBMR01)
Glasgow, Scotland, Dr Matt Fitzpatrick
www.prstatistics.com/course/species-distribution-models-using-r-sdmr01/

13. October 5th – 9th
ECOLOGICAL NICHE MODELLING USING R (ENMR04)
Glasgow, Scotland, Dr. Neftali Sillero
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr04/

14. October 11th – 16th
ADVANCED ECOLOGICAL NICHE MODELLING USING R (ABNMR01)
Glasgow, Scotland, Dr. Neftali Sillero
http://www.prstatistics.com/course/advanced-ecological-niche-modelling-using-r-anmr01/

-- 
Oliver Hooker PhD.
PR statistics

2019 publications;

A way forward with eco evo devo: an extended theory of resource
polymorphism with postglacial fishes as model systems. Biological
Reviews (2019).

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