Current Practices in Data Analysis Procedures in Psychology: What Has Changed?

dc.contributor.authorBlanca Mena, M. José
dc.contributor.authorAlarcón Postigo, Rafael
dc.contributor.authorBono Cabré, Roser
dc.date.accessioned2019-11-11T18:20:55Z
dc.date.available2019-11-11T18:20:55Z
dc.date.issued2018-12-13
dc.date.updated2019-11-11T18:20:56Z
dc.description.abstractThis paper analyzes current practices in psychology in the use of research methods and data analysis procedures (DAP) and aims to determine whether researchers are now using more sophisticated and advanced DAP than were employed previously. We reviewed empirical research published recently in prominent journals from the USA and Europe corresponding to the main psychological categories of Journal Citation Reports and examined research methods, number of studies, number and type of DAP, and statistical package. The 288 papers reviewed used 663 different DAP. Experimental and correlational studies were the most prevalent, depending on the specific field of psychology. Two-thirds of the papers reported a single study, although those in journals with an experimental focus typically described more. The papers mainly used parametric tests for comparison and statistical techniques for analyzing relationships among variables. Regarding the former, the most frequently used procedure was ANOVA, with mixed factorial ANOVA being the most prevalent. A decline in the use of non-parametric analysis was observed in relation to previous research. Relationships among variables were most commonly examined using regression models, with hierarchical regression and mediation analysis being the most prevalent procedures. There was also a decline in the use of stepwise regression and an increase in the use of structural equation modeling, confirmatory factor analysis, and hierarchical linear modeling. Overall, the results show that recent empirical studies published in journals belonging to the main areas of psychology are employing more varied and advanced statistical techniques of greater computational complexity.
dc.format.extent12 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec683372
dc.identifier.issn1664-1078
dc.identifier.pmid30618979
dc.identifier.urihttps://hdl.handle.net/2445/144517
dc.language.isoeng
dc.publisherFrontiers Media
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.3389/fpsyg.2018.02558
dc.relation.ispartofFrontiers in Psychology, 2018, vol. 9, p. 2568
dc.relation.urihttps://doi.org/10.3389/fpsyg.2018.02558
dc.rightscc-by (c) Blanca, María José et al., 2018
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es
dc.sourceArticles publicats en revistes (Psicologia Social i Psicologia Quantitativa)
dc.subject.classificationAnàlisi multivariable
dc.subject.classificationInvestigació quantitativa
dc.subject.classificationAnàlisi de regressió
dc.subject.otherMultivariate analysis
dc.subject.otherQuantitative research
dc.subject.otherRegression analysis
dc.titleCurrent Practices in Data Analysis Procedures in Psychology: What Has Changed?
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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