WiMa-Praktikum (Statistical methods and applications in R and SAS)

Material from the lecture "WiMa-Praktikum II Stochastik" Spring 2016

• The folder lectures contains the slides, either in pdf or html. illustrations contains some data sets and source files (in R and/or SAS) used in the lectures. The csv files are all available in different R packages cited below and reproduced here for being read in SAS.

• The folder exercises contains the exercises given to the students. 2 groups per week then presented their solutions.

Installation

Either click on Download ZIP or clone the repository

$ git clone https://github.com/aallignol/WiMa_Praktikum_II.git

Compilation of the lectures

A makefile is included in lectures for automatic generation of the slides (either pdf or html). The html slides use the reveal.js framework. You may have to change the path of the reveal.js files in the makefile. The slides are compiled using knitr and pandoc or LaTeX.

Program

• Introduction to R and SAS and to reproducible research
• Graphics in R and SAS
• Simple inference, parametric and non-parametric tests
• Linear regression
• Generalized linear model
• Mixed models
• Survival analysis
• Recursive partitioning
• Variable selection and assessment of model performance
• Missing values

References

The following references and sources were used for the development of this course.

• A handbook of statistical analyses using R, third edition

  Torsten Hothorn and Brian S. Everitt

  CRC Press 2014

• Linear Models with R,

  Julian J. Faraway

  Chapman & Hall/CRC

• Extending the Linear Model with R

  Julian J. Faraway

  Chapman & Hall/CRC

• The Elements of Statistical Learning

  Trevor Hastie, Robert Tibshirani, Jerome Freedman

  Springer

• An Introduction to Statistical Learning

  Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani

  Springer

• Survival analysis, techniques for censored and truncated data, second edition

  John P. Klein, Melvin L. Moeschberger

  Springer

• Applied survival analysis using R

  Dirk F Moore

  Springer

• Linear mixed-effects models using R

  Andrzej Galecki, Thomasz Burzykowski

  Springer

• http://www.math.chalmers.se/Stat/Grundutb/GU/MSG500/A13/Lecture10.pdf

• http://socserv.socsci.mcmaster.ca/jfox/Courses/soc740/lecture-5-notes.pdf

• http://www.econ.uiuc.edu/~wsosa/econ471/GLSHeteroskedasticity.pdf

• http://www.gs.washington.edu/academics/courses/akey/56008/lecture/lecture9.pdf

• http://data.princeton.edu/wws509/

• http://socserv.socsci.mcmaster.ca/jfox/Courses/soc740/lecture-11-notes.pdf

• http://socserv.socsci.mcmaster.ca/jfox/Courses/soc761/mixed-models.pdf

• http://kbroman.org/Tools4RR/assets/lectures/01_intro.pdf

• http://www.stat.cmu.edu/~cshalizi/statcomp/14/