Further reading
For depth on particular kinds of modelling, which this guide deliberately skips, some standard starting points:
- Richard McElreath, Statistical Rethinking: A Bayesian Course with Examples in R and Stan, 2nd ed. (McElreath 2020). An excellent, intuition-first introduction to Bayesian modelling.
- Gerry Quinn & Michael Keough, Experimental Design and Data Analysis for Biologists. (Quinn and Keough 2002). A solid reference for design and analysis in ecology.
- Malcolm Haddon, Modelling and Quantitative Methods in Fisheries, 2nd ed. (Haddon 2010). For fisheries and quantitative population modelling.
- Andrew Gelman and colleagues. (Gelman and Hill 2006) and (Gelman et al. 2013). The hierarchical-modelling work that has crossed so productively into ecology.
- Bill Shipley, Cause and Correlation in Biology: A User’s Guide to Path Analysis, Structural Equations and Causal Inference with R, 2nd ed. (Shipley 2016).
References
Gelman, Andrew, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. 2013. Bayesian Data Analysis. 3rd ed. Chapman; Hall/CRC. https://doi.org/10.1201/b16018.
Gelman, Andrew, and Jennifer Hill. 2006. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. https://doi.org/10.1017/CBO9780511790942.
Haddon, Malcolm. 2010. Modelling and Quantitative Methods in Fisheries. 2nd ed. Chapman; Hall/CRC. https://doi.org/10.1201/9781439894170.
McElreath, Richard. 2020. Statistical Rethinking: A Bayesian Course with Examples in r and Stan. 2nd ed. Chapman; Hall/CRC. https://doi.org/10.1201/9780429029608.
Quinn, Gerry P., and Michael J. Keough. 2002. Experimental Design and Data Analysis for Biologists. Cambridge University Press. https://doi.org/10.1017/CBO9780511806384.
Shipley, Bill. 2016. Cause and Correlation in Biology: A User’s Guide to Path Analysis, Structural Equations and Causal Inference with r. 2nd ed. Cambridge University Press. https://doi.org/10.1017/CBO9781139979573.