Statistics Module 2: Linear Models and Linear Mixed Models with R

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Statistics Module 2: Linear Models and Linear Mixed Models with R

  • Beginning: Dec 11, 2017
  • End: Dec 14, 2017
  • Speaker: Dr. Fränzi Korner-Nievergelt
  • Oikostat
  • Location: Seewiesen
  • Room: Seminar Room House 4
  • Host: IMPRS for Organismal Biology
  • Contact: mhieber@orn.mpg.de
Linear models (LM) and linear mixed models (LME): Linear Regression, multiple Regression, ANOVA, ANCOVA, model selection (group work), linear mixed models, work on own data
    Day 1 LM: Linear Regression, multiple Regression, ANOVA, ANCOVA
    • least-square method
    • parameterisation
    • interactions
    • tests (marginal and sequential)
    • model assumptions
    • predictions
    • introduction to Bayesian data analysis
    • posterior distributions
    Day 2 LME: model selection (group work), linear mixed models
    • maximum likelihood, restricted maximum likelihood
    • random and fixed effects
    • likelihood ratio test / bootstrap
    • random slopes-random intercept models
    • possibly further model types depending on the participants wishes
    Day 3 LME:
    • model matrix
    • predictions, posterior probabilities of hypotheses
    • preparing data for work on own data
    Day 4 projects: work on own data and presentations

    Prerequisite for participation: basic knowledge in statistics

    Course material book: Korner-Nievergelt, F., T. Roth, S. Von Felten, J. Guélat, B. Almasi, and P. Korner-Nievergelt. 2015. Bayesian Data Analysis in Ecolog Using Linear Models with R, BUGS, and Stan. Elsevier, New York.

     
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