"Advancing in Statistical Modelling using R"]
Delivered by Dr. Luc Bussiere and Dr. Tom Houslay
http://prstatistics.com/course/advancing-in-statistical-modelling-using-r-advr/
This course will run from 2nd – 6th May 2016 at Malhamtarn Field Station, North Yorkshire, England
This is an introduction to model selection and simplification, mixed effects models, generalised linear models and non-linear models.
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 [log in to unmask] or visit our website www.prstatistics.com
Please feel free to distribute this material anywhere you feel is suitable
Upcoming courses - email for details [log in to unmask]
SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (APRIL)
TIMES SERIES DATA ANALYSIS FOR ECOLOGISTS AND CLIMATOLOGISTS (May)
INTRODUCTION TO PYTHON FOR BIOLOGISTS (May)
ADVANCES IN DNA TAXONOMY USING R (August)
GENETIC DATA ANALYSIS USING R (August)
INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August)
MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (October)
LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (October)
APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (October)
Dates still to be confirmed - email for details [log in to unmask]
STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS
PHYLOGENETIC DATA ANALYSIS USING R
BIONFROMATICS FOR GENETICISTS AND BIOLOGISTS
Oliver Hooker
PR Statistics
