Examining the robustness of a model selection procedure in the binary latent block model through a language placement test data set

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Autori principali: Brault, Vincent, Letué, Frédérique, Martinez, Marie-José
Natura: Preprint
Pubblicazione: 2024
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author Brault, Vincent
Letué, Frédérique
Martinez, Marie-José
author_facet Brault, Vincent
Letué, Frédérique
Martinez, Marie-José
contents When entering French university, the students' foreign language level is assessed through a placement test. In this work, we model the placement test results using binary latent block models which allow to simultaneously form homogeneous groups of students and of items. However, a major difficulty in latent block models is to select correctly the number of groups of rows and the number of groups of columns. The first purpose of this paper is to tune the number of initializations needed to limit the initial values problem in the estimation algorithm in order to propose a model selection procedure in the placement test context. Computational studies based on simulated data sets and on two placement test data sets are investigated. The second purpose is to investigate the robustness of the proposed model selection procedure in terms of stability of the students groups when the number of students varies.
format Preprint
id arxiv_https___arxiv_org_abs_2409_00470
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Examining the robustness of a model selection procedure in the binary latent block model through a language placement test data set
Brault, Vincent
Letué, Frédérique
Martinez, Marie-José
Methodology
Computation
62D99, 62F35, 62K25
G.3
When entering French university, the students' foreign language level is assessed through a placement test. In this work, we model the placement test results using binary latent block models which allow to simultaneously form homogeneous groups of students and of items. However, a major difficulty in latent block models is to select correctly the number of groups of rows and the number of groups of columns. The first purpose of this paper is to tune the number of initializations needed to limit the initial values problem in the estimation algorithm in order to propose a model selection procedure in the placement test context. Computational studies based on simulated data sets and on two placement test data sets are investigated. The second purpose is to investigate the robustness of the proposed model selection procedure in terms of stability of the students groups when the number of students varies.
title Examining the robustness of a model selection procedure in the binary latent block model through a language placement test data set
topic Methodology
Computation
62D99, 62F35, 62K25
G.3
url https://arxiv.org/abs/2409.00470