Statistical data analysis - Christoph Scherber
Last updates: 23rd July 2015
Please note that the course Linear Statistical Models with R will be held by my colleagues, Ingo Grass and Catrin Westphal, in October 2015.
- Workshops &
Courses - Introduction to Statistics
and R - R scripts
& Code - YouTube
Channel
October 2014
PhD course "Linear statistical models with R", Room L318, Grisebachstrasse 6, 6th-10th October
June 2014
Workshop with John Fox on structural equation modelling on 6th June 2014. John Fox is an eminent expert in linear statistical models and he´s written books such as An R Companion to Applied Regression.
April 2014
Workshop by Christoph Scherber "Structural equation models in the Soil Sciences", Deutsche Bodenkundliche Gesellschaft
February 2014
Workshop "Structural Equation models" organized by C. Scherber. Guest speakers and lecturers:
James B. Grace (USGS)
W. Daniel Kissling (Denmark & The Netherlands)
Niels J. Blunch (Denmark)
Statistical graphics
Using R in combination with Adobe Illustrator CS6 for professional graphics outputpublished in Software Developer´s Magazine 4/2012.
General introductions to R and to statistical data analysis
An Introduction to Statistical Data analysis
Linear models
An introduction to mixed effects models
Basic model formulae for mixed-effects models in R
Non-linear mixed-effects models in R
An introduction to generalized linear models
Linear models in matrix notation
Christoph´s mixed R functions
This is a continuously updated file containing useful snippets of R code.
General collection of useful R functions, Version 2015-01-22
Multinomial models
When fitting multinomial models with the nnet package (multinom() function), it is sometimes desirable to increase the number of weights (especially when there is a large number of response categories). This may happen for example in the analysis of next-generation sequencing data. The Anova() function from John Fox´s package "car" can not deal with the MaxNWts argument and hence cannot be used for multinomial models with user-specified maximum number of weights. Below, I provide a function called Anova.multinom2, which allows MaxNWts to be set to any desirded number.
Anova for models with user-specified weights, fitted with the multinom() function
Nonlinear regression
In nonlinear regression situations, one often wishes to use power law functions of the form y=a+b*x^c. The following code allows starting estimates for this function to be estimated automatically.
Self-starting non-linear power law function in R
Model selection
StepAICc function for linear, generalized linear and mixed models
selMod function for model selection in mixed models
Contrast matrices
Working with orthogonal contrasts in R
Test for orthogonality of a contrast matrix
Linear mixed models
Extract lme ANOVAs from multiple models
Extract lme summaries from multiple models
Generalized linear mixed models
Time series analysis
A short introduction to time-series analysis in R
Graphics
Creating publication-quality R Graphics
Ecological diversity
Calculate Shannon´s diversity index
Seed bank data analysis
Analyzing data from a seed bank study using R
Please contact me if you feel there are things that would need to be corrected. R is open-source and new libraries are published every other day, and so it is always a challenging task to keep up with all new developments.
Thanks to the R Core Development Team for making R possible, and also to Mick Crawley for introducing me to R. For downloading and installing R, please visit the R Project website.