The Choice of Control Variables : How Causal Graphs Can Inform the Decision
Abstract
Control variables have a central role when empirical data are used to support causal claims in management research. The current literature has been intransparent in so far as to how control variables should be chosen, how many control variables should be chosen and whether a potential control variable should be included. Causal diagrams provide a transparent framework on how to select control variables for causal identification. This article delineates how causal graphs can inform researchers in leadership and management in finding the correct set of control variables and possible solutions in the case that causal identification is not possible or when causal identification requires unobserved variables.
Main Authors
Format
Conferences
Conference paper
Published
2022
Series
Subjects
Publication in research information system
Publisher
Academy of Management
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202303102117Käytä tätä linkitykseen.
Review status
Peer reviewed
ISSN
0065-0668
DOI
https://doi.org/10.5465/AMBPP.2022.294
Conference
Academy of Management Annual Meeting
Language
English
Published in
Academy of Management Annual Meeting Proceedings
Is part of publication
Academy of Management Proceedings 2022
Citation
- Hünermund, P., Louw, B., & Rönkkö, M. (2022). The Choice of Control Variables : How Causal Graphs Can Inform the Decision. In Academy of Management Proceedings 2022 (2022). Academy of Management. Academy of Management Annual Meeting Proceedings. https://doi.org/10.5465/AMBPP.2022.294
License
Copyright© 2022 Academy of Management