Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency Tables

For the analysis of square contingency tables, the primary objective is to estimate an unknown distribution from presented data. To achieve this objective, we generally use a statistical model that fits the presented data well and has a parsimony. The recently proposed quasi local odds symmetry (QLO...

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Main Author: Shuji Ando
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Symmetry
Subjects:
Online Access:https://www.mdpi.com/2073-8994/14/5/1031
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author Shuji Ando
author_facet Shuji Ando
author_sort Shuji Ando
collection DOAJ
description For the analysis of square contingency tables, the primary objective is to estimate an unknown distribution from presented data. To achieve this objective, we generally use a statistical model that fits the presented data well and has a parsimony. The recently proposed quasi local odds symmetry (QLOS) model was compared to various models that represent the structure of symmetry or asymmetry, and it provided the best fit performance compared with other models for real data. However, the QLOS model has many parameters, that is, the QLOS model is not the parsimonious model. To address this issue, this study proposes a new model that is more parsimonious than the QLOS model. The proposed model is identical to the QLOS model under the specified condition; it is the asymmetry model based on the QLOS model.Moreover, we compare the proposed model with the existing models, including the QLOS model, and show that the proposed model provides better fit performance than the existing models for real datasets.
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spelling doaj.art-8f9410858056451c9e22daa97fe2e2382023-11-23T13:20:17ZengMDPI AGSymmetry2073-89942022-05-01145103110.3390/sym14051031Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency TablesShuji Ando0Department of Information Sciences, Faculty of Science and Technology, Tokyo University of Science, Chiba 278-8510, JapanFor the analysis of square contingency tables, the primary objective is to estimate an unknown distribution from presented data. To achieve this objective, we generally use a statistical model that fits the presented data well and has a parsimony. The recently proposed quasi local odds symmetry (QLOS) model was compared to various models that represent the structure of symmetry or asymmetry, and it provided the best fit performance compared with other models for real data. However, the QLOS model has many parameters, that is, the QLOS model is not the parsimonious model. To address this issue, this study proposes a new model that is more parsimonious than the QLOS model. The proposed model is identical to the QLOS model under the specified condition; it is the asymmetry model based on the QLOS model.Moreover, we compare the proposed model with the existing models, including the QLOS model, and show that the proposed model provides better fit performance than the existing models for real datasets.https://www.mdpi.com/2073-8994/14/5/1031local odds ratiomodel selectionparsimonyquasi symmetry
spellingShingle Shuji Ando
Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency Tables
Symmetry
local odds ratio
model selection
parsimony
quasi symmetry
title Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency Tables
title_full Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency Tables
title_fullStr Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency Tables
title_full_unstemmed Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency Tables
title_short Asymmetry Model Based on Quasi Local Odds Symmetry for Square Contingency Tables
title_sort asymmetry model based on quasi local odds symmetry for square contingency tables
topic local odds ratio
model selection
parsimony
quasi symmetry
url https://www.mdpi.com/2073-8994/14/5/1031
work_keys_str_mv AT shujiando asymmetrymodelbasedonquasilocaloddssymmetryforsquarecontingencytables