Journal of European Psychology Students (Dec 2018)

Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance

  • Koen Derks,
  • Julian Burger,
  • Johnny van Doorn,
  • Jolanda J. Kossakowski,
  • Dora Matzke,
  • Ludovica Atticciati,
  • Julia Beitner,
  • Viket Benzesin,
  • Anne L. de Bruijn,
  • Tara R. H. Cohen,
  • Elisa P. A. Cordesius,
  • Marit van Dekken,
  • Nora Delvendahl,
  • Simone Dobbelaar,
  • Eva R. Groenendijk,
  • Merel E. Hermans,
  • Anu P. Hiekkaranta,
  • Ria H. A. Hoekstra,
  • Agnes M. Hoffmann,
  • Sally A. M. Hogenboom,
  • Sercan Kahveci,
  • Irina J. Karaban,
  • Sofieke Kevenaar,
  • Jurriaan L. te Koppele,
  • Anne-wil Kramer,
  • Emese Kroon,
  • Šimon Kucharský,
  • Ricardo Lieuw-On,
  • Gaby Lunansky,
  • Timo P. Matzen,
  • Annemarie Meijer,
  • Annika Nieper,
  • Laura de Nooij,
  • Leonie Poelstra,
  • Wikke J. van der Putten,
  • Alexandra Sarafoglou,
  • Jessica V. Schaaf,
  • Sara A. J. van de Schraaf,
  • Steven van Schuppen,
  • Manon H. M. Schutte,
  • Mitja Seibold,
  • Scarlett K. Slagter,
  • Aishah C. Snoek,
  • Selina Stracke,
  • Zenab Tamimy,
  • Bram Timmers,
  • Han Tran,
  • Elizabeth S. Uduwa-Vidanalage,
  • Laura Vergeer,
  • Linos Vossoughi,
  • Dilan E. Yücel,
  • Eric-Jan Wagenmakers

DOI
https://doi.org/10.5334/jeps.458
Journal volume & issue
Vol. 9, no. 1
pp. 48 – 57

Abstract

Read online

We outline a network method to synthesize a literature overview from search results obtained by multiple team members. Several network statistics are used to create a single representativeness ranking. We illustrate the method with the dispersed literature on a common misinterpretation of analysis of covariance (ANCOVA). The network method yields a top ten list of the most relevant articles that students and researchers can take as a point of departure for a more detailed study on this topic. The proposed methodology is implemented in Shiny, an open-source R package.

Keywords