This function gives the equivalent latent classes which have the same category success probabilities for each category or item.
LC2LG(Q, sequential = FALSE, att.str = NULL)A required \(J \times K\) binary Q-matrix. J represents test length and K represents the number of attributes of this test. Entry 1 at row j and column k represents the \(k^{th}\) attribute is measured by item \(j\), and 0 means item \(j\) does not measure attribute \(k\).
logical; whether the Q-matrix is a Qc-matrix for sequential models?
attribute structure. See GDINA for details.
An item or category by latent class matrix. In the G-DINA model, if item j measures \(Kj\) attributes, \(2^K\) latent classes can be combined into \(2^{Kj}\) latent groups. This matrix gives which latent group each of \(2^K\) latent classes belongs to for each item.
attributepattern(3)
#> A1 A2 A3
#> [1,] 0 0 0
#> [2,] 1 0 0
#> [3,] 0 1 0
#> [4,] 0 0 1
#> [5,] 1 1 0
#> [6,] 1 0 1
#> [7,] 0 1 1
#> [8,] 1 1 1
q <- matrix(scan(text = "0 1 0 1 0 1 1 1 0"),ncol = 3)
q
#> [,1] [,2] [,3]
#> [1,] 0 1 1
#> [2,] 1 0 1
#> [3,] 0 1 0
LC2LG(Q = q)
#> 000 100 010 001 110 101 011 111
#> [1,] 1 1 2 3 2 3 4 4
#> [2,] 1 2 1 3 2 4 3 4
#> [3,] 1 1 2 1 2 1 2 2