In the published article, there was an error regarding the affiliations for Dingjing Shi. As well as having affiliation University of Oklahoma, they should also have University of Virginia.
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Summary
Keywords
instrumental variables (IV), bayesian method, robust method, missing data, selection bias, R package, causal modeling, local average treatment effect
Citation
Shi D, Tong X and Meyer MJ (2020) Corrigendum: A Bayesian Approach to the Analysis of Local Average Treatment Effect for Missing and Non-normal Data in Causal Modeling: A Tutorial With the ALMOND Package in R. Front. Psychol. 11:2156. doi: 10.3389/fpsyg.2020.02156
Received
30 July 2020
Accepted
31 July 2020
Published
04 September 2020
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
11 - 2020
Updates
Copyright
© 2020 Shi, Tong and Meyer.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Dingjing Shi dingjing.shi@gmail.com
This article was submitted to Quantitative Psychology and Measurement, a section of the journal Frontiers in Psychology
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.