Multivariate exploratory data analysis for large databases: An application to modelling firms’ innovation using CIS data
Metadatos
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comunitat-uji-handle2:10234/8645
comunitat-uji-handle3:10234/8646
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INVESTIGACIONMetadatos
Título
Multivariate exploratory data analysis for large databases: An application to modelling firms’ innovation using CIS dataFecha de publicación
2018Editor
ElsevierISSN
2340-9436Cita bibliográfica
BOU-LLUSAR, Juan C.; SATORRA, Albert. Multivariate exploratory data analysis for large databases: An application to modelling firms’ innovation using CIS data. BRQ Business Research Quarterly, 2018Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/pii/S2340943618301695#!Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
This paper argues that, when using a large database, organizational researchers would benefit from the use of specific multivariate exploratory data analysis (MEDA) before performing statistical modelling. Issues such ... [+]
This paper argues that, when using a large database, organizational researchers would benefit from the use of specific multivariate exploratory data analysis (MEDA) before performing statistical modelling. Issues such as the representativeness of the database across domains (countries or sectors), assessment of confounding among categorical covariates, missing data, dimension reduction to produce performance indicators and/or remedy multicollinearity problems are addressed by specific MEDA. The proposed MEDA is applied to data from the Community Innovation Survey (CIS), a large database commonly used to analyse firms’ innovation activities, prior to fitting ordered logit and Tobit regression models. A set of recommended practices involving MEDA are proposed throughout the paper. [-]
Publicado en
BRQ Business Research Quarterly, 2018Proyecto de investigación
Spanish MEC Grants: Grant Number ECO2015-66671-P (MINECO/FEDER), and ECO2014-59885-P; Generalitat Valenciana: Grant Number BEST/2018/209Derechos de acceso
info:eu-repo/semantics/openAccess
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