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--></style></head><body lang=DE link="#0563C1" vlink="#954F72" style='word-wrap:break-word'><div class=WordSection1><p class=MsoNormal>Greetings statnet-users,<o:p></o:p></p><p class=MsoNormal><span lang=EN-US>I have read Hunter et al. 2008 (specifically p. 256ff.) about how AIC may not be the best criterion to evaluate ERGMs and that this is even more true for BIC. However, while I am also reporting and discussing the statistics/visual representations estimated through the gof-function, it is common in my field to report AIC/BIC values in ERGMs and discuss them.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>I am modeling a large two-mode network and am a bit puzzled about the AIC/BIC values, as they are very large. My assumption is that the size of these values is due to the large network (about 9000 “actors” and 500 “groups”). My main question is what to make of the differences in AIC values. In Kim et al. (2016), the AIC value of 1196 compared to 1264 is interpreted as “substantially smaller”. The AIC values in my models are 123352 versus 125383. I am unsure if the absolute or relative difference matters: If the absolute difference matters, then a difference of 2031 would also mean the AIC is “substantially smaller”. If the relative difference matters, than the AIC in my models will have reduced around 1/60<sup>th</sup> versus roughly 1/20<sup>th</sup> in the work I referred in this paragraph.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>Thanks for any advice on this,<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Steffen<o:p></o:p></span></p></div></body></html>