Generate hierarchical attribute structures
This function can be used to generate hierarchical attributes structures, and to provide prior joint attribute distribution with hierarchical structures.
att.structure(hierarchy.list = NULL, K, Q, att.prob = "uniform")
hierarchy.list |
a list specifying the hierarchical structure between attributes. Each
element in this list specifies a DIRECT prerequisite relation between two or more attributes.
See |
K |
the number of attributes involved in the assessment |
Q |
Q-matrix |
att.prob |
How are the probabilities for latent classes simulated? It can be |
att.str reduced latent classes under the specified hierarchical structure
impossible.latentclass impossible latent classes under the specified hierarchical structure
att.prob probabilities for all latent classes; 0 for impossible latent classes
Wenchao Ma, The University of Alabama, wenchao.ma@ua.edu
Jimmy de la Torre, The University of Hong Kong
## Not run: ################# # # Leighton et al. (2004, p.210) # ################## # linear structure A1->A2->A3->A4->A5->A6 K <- 6 linear=list(c(1,2),c(2,3),c(3,4),c(4,5),c(5,6)) att.structure(linear,K) # convergent structure A1->A2->A3->A5->A6;A1->A2->A4->A5->A6 K <- 6 converg <- list(c(1,2),c(2,3),c(2,4), c(3,4,5), #this is how to show that either A3 or A4 is a prerequisite to A5 c(5,6)) att.structure(converg,K) # convergent structure [the difference between this one and the previous one is that # A3 and A4 are both needed in order to master A5] K <- 6 converg2 <- list(c(1,2),c(2,3),c(2,4), c(3,5), #this is how to specify that both A3 and A4 are needed for A5 c(4,5), #this is how to specify that both A3 and A4 are needed for A5 c(5,6)) att.structure(converg2,K) # divergent structure A1->A2->A3;A1->A4->A5;A1->A4->A6 diverg <- list(c(1,2), c(2,3), c(1,4), c(4,5), c(4,6)) att.structure(diverg,K) # unstructured A1->A2;A1->A3;A1->A4;A1->A5;A1->A6 unstru <- list(c(1,2),c(1,3),c(1,4),c(1,5),c(1,6)) att.structure(unstru,K) ## See Example 4 and 5 in GDINA function ## End(Not run)
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