@AmirSariaslan Have you looked into network analysis of the P factor? Could be interesting. Requires item-level datapic.twitter.com/P1TVhIn0pB
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@AmirSariaslan Have you looked into network analysis of the P factor? Could be interesting. Requires item-level datapic.twitter.com/P1TVhIn0pB
@KirkegaardEmil Of course I have - you should follow @EikoFried
@AmirSariaslan @KirkegaardEmil Network model & P are mutually exclusive explan. of covariance among items, no? Common cause vs interaction.
@EikoFried @AmirSariaslan Not at all. Networks are an alternative causal explanation of the existence of the co-variance. :)
@KirkegaardEmil @AmirSariaslan Yes, reflective factor & networks differ in explanation of why items covary (common cause vs. interaction)
@EikoFried @AmirSariaslan Perhaps the P factor is a collective property of the nodes, e.g. avg. strength of relaying bwtn P-nodes.
@EikoFried @AmirSariaslan In my simple simul of a network, g factor ≈ rate of relaying which I interpret as learning https://osf.io/myxfv/files/
@KirkegaardEmil @AmirSariaslan colleague of mine working on similar questions, really cool to see more people investigating that! @rogierK
@EikoFried @AmirSariaslan @rogierK rate of learning in my simul. cor ~0.99 with g factor score. Odd, rate of forgetting does not cor with g.
@KirkegaardEmil @AmirSariaslan @rogierK Emil, I was referring to this p-factor http://cpx.sagepub.com/content/early/2013/08/14/2167702613497473 …. Is that what you meant?
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