A Multidimensional Finite Mixture Structural Equation Model for Nonignorable Missing Responses to Test Items

作者：Bacci Silvia^*; Bartolucci Francesco

来源：Structural Equation Modeling, 2015, 22(3): 352-365.

DOI：10.1080/10705511.2014.937376

• finite mixture models
• student entry test
• semiparametric inference
• item response theory
• EM algorithm

We propose a structural equation model, which reduces to a multidimensional latent class item response theory model, for the analysis of binary item responses with nonignorable missingness. The missingness mechanism is driven by 2 sets of latent variables: one describing the propensity to respond and the other referred to the abilities measured by the test items. These latent variables are assumed to have a discrete distribution, so as to reduce the number of parametric assumptions regarding the latent structure of the model. Individual covariates can also be included through a multinomial logistic parameterization for the distribution of the latent variables. Given the discrete nature of this distribution, the proposed model is efficiently estimated by the expectation-maximization algorithm. A simulation study is performed to evaluate the finite-sample properties of the parameter estimates. Moreover, an application is illustrated with data coming from a student entry test for the admission to some university courses.

• 出版日期2015-7-3
• 单位Perugia