Scientific Programming: Statistical modeling in R (part 2)

Sara Mortara; Andrea Sánchez-Tapia

Slides

Tutorial

Find here the model selection tutorial
Find here the script from the slides
Download here the cuckoo data (from Valletta’s workshop)
Download here the bacteria data (from Valletta’s workshop)

Libraries

To run the code from the slides and the tutorial you’ll need to have installed the packages lme4, merTools, and bbmle.

install.packages("lme4")
install.packages("merTools")
install.packages("bbmle") # for model selection

Basic references

Workshop of Statistical modeling in R from JJ Valleta and TJ McKinley <3
DHARMa package
merTools package
Mixed model guide
Douglas Bates, Martin Maechler, Ben Bolker, Steve Walker (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48. doi:10.18637/jss.v067.i01.
Anderson, D. and Burnham, K., 2004. Model selection and multi-model inference. Second. NY: Springer-Verlag, 63(2020), p.10.
Zuur, A.F., Ieno, E.N., Walker, N.J., Saveliev, A.A. and Smith, G.M., 2009. Mixed effects models and extensions in ecology with R (Vol. 574). New York: Springer.

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

Mortara & Sánchez-Tapia (2022, July 19). Scientific Programming: Statistical modeling in R (part 2). Retrieved from https://scientific-computing.netlify.app/08_statistical_modeling_2.html

BibTeX citation

@misc{mortara2022statistical,
  author = {Mortara, Sara and Sánchez-Tapia, Andrea},
  title = {Scientific Programming: Statistical modeling in R (part 2)},
  url = {https://scientific-computing.netlify.app/08_statistical_modeling_2.html},
  year = {2022}
}