Models for the Assessment of Treatment Improvement: The Ideal and the Feasible

Comparisons of different treatments or production processes are the goals of a significant fraction of applied research. Unsurprisingly, two sample problems play a main role in statistics through natural questions such as. Is the the new treatment significantly better than the old. However, this is...

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Detalles Bibliográficos
Autores: Álvarez-Esteban, P. C., Barrio, E. del, Cuesta Albertos, Juan Antonio|||0000-0001-8228-5924, Matrán, C.
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/13290
Acceso en línea:http://hdl.handle.net/10902/13290
Access Level:acceso abierto
Palabra clave:Stochastic dominance
Similarity
Two-sample comparison
Trimmed distributions
Winsorized distributions
Behrens–Fisher problem
Index of stochastic dominance
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spelling Models for the Assessment of Treatment Improvement: The Ideal and the FeasibleÁlvarez-Esteban, P. C.Barrio, E. delCuesta Albertos, Juan Antonio|||0000-0001-8228-5924Matrán, C.Stochastic dominanceSimilarityTwo-sample comparisonTrimmed distributionsWinsorized distributionsBehrens–Fisher problemIndex of stochastic dominanceComparisons of different treatments or production processes are the goals of a significant fraction of applied research. Unsurprisingly, two sample problems play a main role in statistics through natural questions such as. Is the the new treatment significantly better than the old. However, this is only partially answered by some of the usual statistical tools for this task. More importantly, often practitioners are not aware of the real meaning behind these statistical procedures. We analyze these troubles from the point of view of the order between distributions, the stochastic order, showing evidence of the limitations of the usual approaches, paying special attention to the classical comparison of means under the normal model. We discuss the unfeasibility of statistically proving stochastic dominance, but show that it is possible, instead, to gather statistical evidence to conclude that slightly relaxed versions of stochastic dominance hold.Research partially supported by the Spanish Ministerio de Economía y Competitividad y fondos FEDER, grants MTM2014-56235-C2-1-P and MTM2014-56235-C2-2, and by Consejería de Educación de la Junta de Castilla y León, grant VA212U13.Institute of Mathematical Statistics (IMS)Universidad de Cantabria20172017-01-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttp://hdl.handle.net/10902/13290Statistical Science 2017, Vol. 32, No. 3, 469-485reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/132902026-06-02T12:39:31Z
dc.title.none.fl_str_mv Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
title Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
spellingShingle Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
Álvarez-Esteban, P. C.
Stochastic dominance
Similarity
Two-sample comparison
Trimmed distributions
Winsorized distributions
Behrens–Fisher problem
Index of stochastic dominance
title_short Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
title_full Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
title_fullStr Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
title_full_unstemmed Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
title_sort Models for the Assessment of Treatment Improvement: The Ideal and the Feasible
dc.creator.none.fl_str_mv Álvarez-Esteban, P. C.
Barrio, E. del
Cuesta Albertos, Juan Antonio|||0000-0001-8228-5924
Matrán, C.
author Álvarez-Esteban, P. C.
author_facet Álvarez-Esteban, P. C.
Barrio, E. del
Cuesta Albertos, Juan Antonio|||0000-0001-8228-5924
Matrán, C.
author_role author
author2 Barrio, E. del
Cuesta Albertos, Juan Antonio|||0000-0001-8228-5924
Matrán, C.
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Stochastic dominance
Similarity
Two-sample comparison
Trimmed distributions
Winsorized distributions
Behrens–Fisher problem
Index of stochastic dominance
topic Stochastic dominance
Similarity
Two-sample comparison
Trimmed distributions
Winsorized distributions
Behrens–Fisher problem
Index of stochastic dominance
description Comparisons of different treatments or production processes are the goals of a significant fraction of applied research. Unsurprisingly, two sample problems play a main role in statistics through natural questions such as. Is the the new treatment significantly better than the old. However, this is only partially answered by some of the usual statistical tools for this task. More importantly, often practitioners are not aware of the real meaning behind these statistical procedures. We analyze these troubles from the point of view of the order between distributions, the stochastic order, showing evidence of the limitations of the usual approaches, paying special attention to the classical comparison of means under the normal model. We discuss the unfeasibility of statistically proving stochastic dominance, but show that it is possible, instead, to gather statistical evidence to conclude that slightly relaxed versions of stochastic dominance hold.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10902/13290
url http://hdl.handle.net/10902/13290
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Mathematical Statistics (IMS)
publisher.none.fl_str_mv Institute of Mathematical Statistics (IMS)
dc.source.none.fl_str_mv Statistical Science 2017, Vol. 32, No. 3, 469-485
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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