Multiple Linear Regression versus Automatic Linear Modelling

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dc.contributor.authorGenc, S.
dc.contributor.authorMendes, M.
dc.date.accessioned2025-01-27T21:19:27Z
dc.date.available2025-01-27T21:19:27Z
dc.date.issued2024
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractIn this study, performances of Multiple Linear Regression and Automatic Linear Modelling are compared for different sample sizes and number of predictors. A comprehensive Monte Carlo simulation study was carried out for this purpose. Random numbers generated from multivariate normal distribution by using RNMVN function of IMSL library of Microsoft FORTRAN Developer Studio composed the material of this study. Results of the simulation study showed that the sample size and the number of predictors are the main factors that lead to produce different results. Although both methods gave very similar results especially when studied with large sample sizes (n >= 100), the Automatic linear modelling is preferred for analyzing data sets due to its simplicity in analyzing data and interpreting the results, ability to present results visually and providing more detailed information especially studying large complex data sets. It will be beneficial to use the Automatic linear modelling especially in analyzing massive and complex data sets for the purposes of investigating the relationships between one continuous dependent and 10 or more predictors and determine the factors that affect the response or target variable. At the same time, it will also be possible to evaluate the effect of each predictor with a more detailed response.
dc.identifier.doi10.1590/1678-4162-13071
dc.identifier.endpage136
dc.identifier.issn0102-0935
dc.identifier.issn1678-4162
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85185881434
dc.identifier.scopusqualityQ3
dc.identifier.startpage131
dc.identifier.urihttps://doi.org/10.1590/1678-4162-13071
dc.identifier.urihttps://hdl.handle.net/20.500.12428/28611
dc.identifier.volume76
dc.identifier.wosWOS:001177166600001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherArquivo Brasileiro Medicina Veterinaria Zootecnia
dc.relation.ispartofArquivo Brasileiro De Medicina Veterinaria E Zootecnia
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20250125
dc.subjectmultiple regression
dc.subjectautomatic linear modelling
dc.subjectsimulation
dc.subjectR2
dc.titleMultiple Linear Regression versus Automatic Linear Modelling
dc.title.alternativeRegressão Linear Múltipla versus Modelagem Linear Automática
dc.typeArticle

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