GLMM course

Logistics

• setup instructions
• schedule
• student survey

Notes

• daily notes:
  • Montag
• data vis (HTML, Rmarkdown)
• GLMs: basic (HTML, Rmarkdown)
• GLMs: intermediate (HTML, Rmarkdown)
• GLMM overview (HTML, Rmarkdown)
• philosophy (HTML, Rmarkdown)
• mixed-model details (HTML, Rmarkdown)
• mixed-model lab (HTML, Rmarkdown)
• GLMM details (HTML, Rmarkdown)
• GLMM lab (HTML, Rmarkdown)
• Bayesian computation and inference (HTML, Rmarkdown)
• Bayesian lab (HTML, Rmarkdown)
• addons/extra (HTML, Rmarkdown)

misc R code

• geom_cstar.R
• calcDenDF.R
• histogram.mcmc.R

Data sets

• partly annotated list
• complete zipped file
• GitHub directory

Miscellaneous links

• eco stats example (source)
• GLMM FAQ
• ISEC talk on model averaging
• R resources for (simulation-based or other) power analysis for (G)LMMs:
  • Simulation-related packages: clusterPower, longpower, powerbydesign, powerlmm, WebPower, simr
  • Rpubs links: simpower, zinb_power
  • Kain et al., PeerJ 2017: A practical guide and power analysis for GLMMs
• Frank Harrell's Regression Modeling Strategies on SpringerLink (read chapter 4!)
• Chapter 13 from Fox et al (private link)