"Advancing in Statistical Modelling using R"
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/
Delivered by Dr. Luc Bussiere and Dr. Ane Timenes Laugen
This course will run from 24th – 28th April 2017 at FAFU University,
Fuzhou, China
This is an introduction to model selection and simplification,
generalised linear models, mixed effects models and non-linear models.
]A more introductory will run the week before (Introduction to R and
statistics for biologists) and a discount is available if both courses
are booked at the same time.
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/
The course is aimed at biologists with a basic to moderate knowledge in
R. The course content is designed to bridge the gap between basic R
coding and more advanced statistical modelling. This five day course
will consist of series of modules, each lasting roughly half a day and
comprised of lectures and practicals designed to either build required
skills for future modules or to perform a family of analyses that is
frequently encountered in the biological literature.
Course content is as follows
Day 1 Course introduction
• Techniques for data manipulation, aggregation, and visualisation;
introduction to linear regression. Packages: {tidyr}, {dplyr}, {ggplot2}
Day 2 Linear models
• Diagnostics, collinearity, scaling, plotting fitted values); fitting
and interpreting interaction terms; model selection and simplification;
general linear models and ANCOVA.
• Packages: {stats}, {car}
Day 3 Generalized linear models
• Logistic and Poisson regression; predicting using model objects and
visualizing model fits.
• Packages: {broom}, {visreg}, {ggplot2}
Day 4 Mixed effects models
• Theory and practice of mixed effect models; visualising fixed and
random effects.
• Packages: {lme4}, {broom}, {ggplot2}, {sjPlot}
Day 5 Fitting nonlinear functions
• Polynomial & Mechanistic models; brief introduction to more advanced
topics & combining methods (e.g., generalised linear mixed effects,
nonlinear mixed effects, and zero-inflated and zero-altered models).
• Packages: {nlsTools}.
• Afternoon to discuss own data if time permits
Please email any inquiries to [email protected] or visit our
website www.prstatistics.com
Please feel free to distribute this material anywhere you feel is
suitable
Our other upcoming courses
1. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January
2017) #MBMV
http://www.prstatistics.com/course/model-base-multivariate-analysis-of-abundance-data-using-r-mbmv01/
2. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/
3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
(February 2017) #SIMM
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/
4. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/
5. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April
2017) #MVSP
http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp02/
6. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/
7. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/
8. ECOLOGICAL AND EVOLUTIONARY BIOGEOGRAPHY USING R (May 2017) #EEBR
9. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/
10. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE
http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/
11. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME)
12. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/
13. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/
14. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY
BIOLOGISTS (July 2017 TBC) #SEMR
15. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/
16. INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL
17. GENETIC DATA ANALYSIS USING R (October 2017 TBC) #GDAR
18. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November 2017
TBC) #LNDG
19. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017) #ABME
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/
20. INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS
21. INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB
22. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017)
#DVMP
http://www.prstatistics.com/course/data-visualisation-and-manipulation-using-python-dvmp01/
23. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR
24. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (January 2018) #IBHM
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/
25. PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL
Oliver Hooker PhD.
www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/Oliver Hooker
PR statistics
3/1
128 Brunswick Street
Glasgow
G1 1TF
+44 (0) 7966500340
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