Estimation of Compensatory and Noncompensatory Multidimensional Item Response Models Using Markov Chain Monte Carlo

By D. Bolt, Venessa F. Lall. 2003

190 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/70a6a5d158c1230ab9eb1060d1e60a1516582964

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Paradoxical Results in Multidimensional Item Response Theory (2009, background): “mulative distribution function and aij 1 > 0 ( Bolt and Lall, 2003; Whitely, 1980).”
Performances of LOO and WAIC as IRT Model Selection Methods (2017, methodology): “With an expanding body of literature on Bayesian IRT (e.g., Beguin & Glas, 2001; Bolt & Lall, 2003; Cao & Stokes, 2008; Fox & Glas, 2003; Jiao & Zhang, 2015), the topic of Bayesian model checks and comparison in the IRT context has also received increasing attention (e.g., Levy, Mislevy, &…”
IRT Model Selection Methods for Dichotomous Items (2007, unknown): “According to Bolt and Lall (2003), the likelihood of the Ycv for a model is then computed using the updated posterior distribution as a prior: PðYcvjModelÞ= Z PðYcvjθi;Ycal;ModelÞfθðθijYcal;ModelÞdθi; ð5Þ PðYcvjθi;Ycal;ModelÞ represents the conditional likelihood, and fθðθijYcal;ModelÞ is the…”
Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art (2008, background): “Thus, the multicomponent trait model and its extension (Embretson, 1991) and noncompensatory multidimensional IRT models (Bolt & Lall, 2003), which contain continuous latent variables, are structurally similar to noncompensatory DCM, even though DCM contain discrete latent variables.”
Latent Variable Selection for Multidimensional Item Response Theory Models via $$L_{1}$$L1 Regularization (2016, unknown): “The other is to set a j j = 1 and a jk = 0 for j = 1, . . . , K , k = 1, . . . , K , and j = k. Note that for the former constraint, rotating the parameter space is usually necessary for the interpretation of the factor patterns (Bolt & Lall, 2003; Cai, 2010).”