Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance
oleh: 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
| Format: | Article |
|---|---|
| Diterbitkan: | European Federation of Psychology Students' Associations 2018-12-01 |
Deskripsi
<p class="p1">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.</p>