Causal effect for ordinal outcomes from observational data: Bayesian approach
© 2016 by the Mathematical Association of Thailand. All rights reserved. Ordinal outcomes are often observed in the social and economic sciences. It is frequently that the scale or magnitude of the outcomes is not available. The common average treatment effect is not well-defined for causal inferenc...
Saved in:
Main Authors: | Sirisrisakulchai J., Sriboonchitta S. |
---|---|
Format: | Journal |
Published: |
2017
|
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85008318891&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42333 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
Similar Items
-
Causal effect for ordinal outcomes from observational data: Bayesian approach
by: Jirakom Sirisrisakulchai, et al.
Published: (2018) -
CAUSAL INFERENCE FROM OBSERVATIONAL DATA
by: VO THANH VINH
Published: (2022) -
Bayesian approach to multivariate component-based logistic regression: Analyzing correlated multivariate ordinal data
by: Ju-Hyun Park, et al.
Published: (2022) -
Modeling dependence of accident-related outcomes using pair copula constructions for discrete data
by: Sirisrisakulchai J., et al.
Published: (2014) -
Learning with ordinal-bounded memory from positive data
by: Carlucci, L., et al.
Published: (2013)