AIC model selection using Akaike weights

@georg_henning Not a significance test but this could help: https://t.co/Ww6zvtDQOH

@eric_knowles @sccacace Another relative comparison: Information criteria weights (e.g., wBIC). https://t.co/W911Fh1jg0

@MarkAnnuncio See https://t.co/G02MQdcXEu and https://t.co/bPN72jF8K8

@PhDemetri Maybe this helps? Wagenmakers and Farrell (2004). AIC model selection using Akaike weights. https://t.co/39g7YMTe1w

RT @JosephCrispell: What can be learnt from looking at Akaike Information Criterion (#AIC) weights as well as scores? https://t.co/r3cHB8GA…

What can be learnt from looking at Akaike Information Criterion (#AIC) weights as well as scores? https://t.co/r3cHB8GAJq https://t.co/VfAa7CUNh7

@olijrobinson You can compute (I think) DIC weights in the same way as Akaike weights/Schwarz weights, see here https://t.co/Op6eYXKbWw implemented in the package qpcr https://t.co/dWRL1T23OC but I know that the DIC makes people very angry, so I would stic

@dingding_peng @wdonald_1985 That is a sensible strategy. I like this paper https://t.co/Op6eYXKbWw and this for general background https://t.co/VKpWv2ybrw