This is a repository for the joint lab meeting project to work through the Dormann et al. paper on model averaging. https://doi.org/10.1002/ecm.1309
Two datasets were created: one with a Bernoulli response and one with a Normal response. Each dataset has a number of potential predictor variables. The task is to create model-averaged estimates of predictions using the methods described in Dormann et al.
Fake data story (logit): We tested N = 100 nudibranchs to see if they failed (0) or succeeded (1) in solving a maze. There are 8 covariates associated to varying degrees with nudibranch maze-solving ability (I expect to hear suggestions as to what these might be when we meet).
Fake data story (normal): We measured N = 100 nudibranchs to determine how much 8 covariates could help explain their size (in cm). We wish to farm nudibranchs and want to know how to perfect conditions in our tanks to achieve hefty nudibranchs.