Four datasets to play with for a hackathon to practice skills learnt at the Deakin Bayesian Statistics Worshop 2022
Source: Main et al., 2020 (https://doi.org/10.1111/ddi.13115)
Description: Meta-analysis of fox homerange sizes with a range of predictor variables.
Result: Human impact overrides bioclimatic drivers of red fox home range size globally.
Files:
a) "MAIN_foxes_readme.txt" - original documentation of the dataset
b) "fox_data.csv" - the dataset
c) "Dataset1_redFoxHomeRange.R" - code to read it and a couple of data explorations
d) "fox_code.R" - code to replicate the analyses presented in the paper
e) "Main et al 2020.pdf" - paper published in Div&Dist
Suggested analysis: Gaussian (log) regression
Source: Elith et al., 2020 (https://doi.org/10.17161/bi.v15i2.13384)
Description: Presence-absence (1-0) data for 20 bird species in South-East Canada with environment predictors either already extracted or as rasters. Package "disdat".
Files:
a) "CanadianBirdDistributions.R" - code to read it and a couple of data explorations
b) "Elith et al_BI_2020.pdf" - original paper published in Biodiv. Informatics
c) "rasters_Can.zip" - compressed file with the original rasters of the environmental predictors
(note that altitude was not included as raster but it still is present in the extracted values)
Suggested analysis: Bernoulli (logit) regression
Source: Wille et al., preprint (https://doi.org/10.1101/2022.02.14.480463)
Description: Investigating the phylogenetic and ecological effects on host competency for avian influenza in Australian wild birds.
Files:
a) "2022.02.14.480463v1.full.pdf" - Preprint paper published in bioRxiv.
b) "birddata.csv" - the dataset
c) "phylogeneticTree_allSpecies.nwk" - the phylogenetic tree
d) "Dataset3_AvianInfluenza.R" - code to read it, clean it and a couple of data explorations
e) "AIVOzGLMPhylo20220120.Rmd" - original code to run the analyses in Wille et al preprint
Suggested analysis: Bernoulli (logit) regression for A
Source: Julia Ryeland and Matt Symonds
Description: observations of shorebird roosting behaviour and roosting time standing on one leg for 9 bird species predicted by environmental conditions with random and fixed effect. Bayesian modelling approach described within the paper.
Files:
a) "Roostingdata.csv" original dataset - whats in there is unclear
b) "Dataset4_OneLegRoosting.R" - code to load the data
c) "Journal of Avian Biology - 2019 - Ryeland - Leg length and temperature determine the use of unipedal roosting in birds.pdf" - Paper published in Journal of Avian Biology
Suggested analysis: look at the papers approach