This article is a correction to:
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
Dingjing Shi
Xin Tong
M. Joseph Meyer- 1Department of Psychology, University of Oklahoma, Norman, OK, United States
- 2Department of Psychology, University of Virginia, Charlottesville, VA, United States
by Shi, D., Tong, X., and Meyer, M. J. (2020). Front. Psychol. 11:169. doi: 10.3389/fpsyg.2020.00169
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.
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, SwitzerlandCopyright © 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