https://ogma.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:14086 Wed 11 Apr 2018 16:54:17 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:11033 Wed 11 Apr 2018 14:33:27 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:13857 Wed 11 Apr 2018 12:43:20 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9526 Wed 11 Apr 2018 10:35:15 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:6213 Wed 11 Apr 2018 09:36:32 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:1183 Sat 24 Mar 2018 08:28:26 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19064 Sat 24 Mar 2018 08:05:25 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21814 Journal of Mathematical Psychology, 19, 137–181, 1979) is a graphical analysis that can determine whether one or more than one latent variable mediates an apparent dissociation between the effects of two experimental manipulations. State-trace analysis makes only ordinal assumptions and so, is not confounded by range effects that plague alternative methods, especially when performance is measured on a bounded scale (such as accuracy). We describe and illustrate the application of a freely available GUI driven package, StateTrace, for the R language. StateTrace automates many aspects of a state-trace analysis of accuracy and other binary response data, including customizable graphics and the efficient management of computationally intensive Bayesian methods for quantifying evidence about the outcomes of a state-trace experiment, developed by Prince, Brown, and Heathcote (Psychological Methods, 17, 78–99, 2012).]]> Sat 24 Mar 2018 07:58:40 AEDT ]]>