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A Formal Treatment of Sequential Ignorability

Taking a rigorous formal approach, we consider sequential decision problems involving observable variables, unobservable variables, and action variables. We can typically assume the property of extended stability, which allows identification (by means of “[Formula: see text] -computation”) of the co...

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Detalles Bibliográficos
Autores principales: Dawid, A. Philip, Constantinou, Panayiota
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4245505/
https://www.ncbi.nlm.nih.gov/pubmed/25484994
http://dx.doi.org/10.1007/s12561-014-9110-8
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author Dawid, A. Philip
Constantinou, Panayiota
author_facet Dawid, A. Philip
Constantinou, Panayiota
author_sort Dawid, A. Philip
collection PubMed
description Taking a rigorous formal approach, we consider sequential decision problems involving observable variables, unobservable variables, and action variables. We can typically assume the property of extended stability, which allows identification (by means of “[Formula: see text] -computation”) of the consequence of a specified treatment strategy if the “unobserved” variables are, in fact, observed—but not generally otherwise. However, under certain additional special conditions we can infer simple stability (or sequential ignorability), which supports [Formula: see text] -computation based on the observed variables alone. One such additional condition is sequential randomization, where the unobserved variables essentially behave as random noise in their effects on the actions. Another is sequential irrelevance, where the unobserved variables do not influence future observed variables. In the latter case, to deduce sequential ignorability in full generality requires additional positivity conditions. We show here that these positivity conditions are not required when all variables are discrete.
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spelling pubmed-42455052014-12-03 A Formal Treatment of Sequential Ignorability Dawid, A. Philip Constantinou, Panayiota Stat Biosci Article Taking a rigorous formal approach, we consider sequential decision problems involving observable variables, unobservable variables, and action variables. We can typically assume the property of extended stability, which allows identification (by means of “[Formula: see text] -computation”) of the consequence of a specified treatment strategy if the “unobserved” variables are, in fact, observed—but not generally otherwise. However, under certain additional special conditions we can infer simple stability (or sequential ignorability), which supports [Formula: see text] -computation based on the observed variables alone. One such additional condition is sequential randomization, where the unobserved variables essentially behave as random noise in their effects on the actions. Another is sequential irrelevance, where the unobserved variables do not influence future observed variables. In the latter case, to deduce sequential ignorability in full generality requires additional positivity conditions. We show here that these positivity conditions are not required when all variables are discrete. Springer US 2014-04-08 2014 /pmc/articles/PMC4245505/ /pubmed/25484994 http://dx.doi.org/10.1007/s12561-014-9110-8 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/2.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Dawid, A. Philip
Constantinou, Panayiota
A Formal Treatment of Sequential Ignorability
title A Formal Treatment of Sequential Ignorability
title_full A Formal Treatment of Sequential Ignorability
title_fullStr A Formal Treatment of Sequential Ignorability
title_full_unstemmed A Formal Treatment of Sequential Ignorability
title_short A Formal Treatment of Sequential Ignorability
title_sort formal treatment of sequential ignorability
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4245505/
https://www.ncbi.nlm.nih.gov/pubmed/25484994
http://dx.doi.org/10.1007/s12561-014-9110-8
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