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liboscats Reference Manual | ![]() |
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Top | Description | Object Hierarchy | Properties |
struct OscatsModelHetlgr;
The Heterogeneous Logistic Graded Response IRT model is a generalization of the Homogeneous Logistic Graded Response model (OscatsModelGr) that allows the discrimination of each response category to be different: P(X=k|theta) = P*_k(theta) - P*_{k+1}(theta), P*_k(theta) = 1/1+exp[-(sum_i a_ki theta_i - b_k + sum_j d_j covariate_j)] where P*_k(theta) = P(X>=k|theta) is the probability of scoring at least k, P*_0(theta) = 1, P*_{Ncat} = 0, a_ki is the discrimination on dimension i for response k, and b_k is the scaled response boundary location. Responses are numbered 0, 1, ..., Ncat-1. Note that all respose options share the same parameters for the covariates. No distance metric is currently provided, but see Ali (2011) for possibilities.
Parameter names: Diff.k, Discr.k.DimName
References:
1976). "The graded response model of latent trait theory and tailored testing." Proceedings of the First Conference on Computerized Adaptive Testing, 5-15.
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"Ncat"
property"Ncat" guint : Read / Write / Construct Only
The number of response categories in the IRT model, numered 0, 1, ..., Ncat-1. The default number of categories is 3, which is also the minimum.
Allowed values: >= 3
Default value: 3