Kernel Function in Local Linear Peters-Belson Regression
Determining the extent of a disparity, if any, between groups of people, for example, race or gender, is of interest in many fields, including public health for medical treatment and prevention of disease or in discrimination cases concerning equal pay to estimate the pay disparities between minorit...
- Autores:
-
Bolbolian Ghalibaf, Mohammad
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/66486
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/66486
http://bdigital.unal.edu.co/67514/
- Palabra clave:
- 51 Matemáticas / Mathematics
31 Colecciones de estadística general / Statistics
Kernel Function
Local Linear Peters-Belson Regression
Majority Group
Minority Group
Welch's Approximation.
Aproximación de Welch
función kernel
regresión lineal local
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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dc.title.spa.fl_str_mv |
Kernel Function in Local Linear Peters-Belson Regression |
title |
Kernel Function in Local Linear Peters-Belson Regression |
spellingShingle |
Kernel Function in Local Linear Peters-Belson Regression 51 Matemáticas / Mathematics 31 Colecciones de estadística general / Statistics Kernel Function Local Linear Peters-Belson Regression Majority Group Minority Group Welch's Approximation. Aproximación de Welch función kernel regresión lineal local |
title_short |
Kernel Function in Local Linear Peters-Belson Regression |
title_full |
Kernel Function in Local Linear Peters-Belson Regression |
title_fullStr |
Kernel Function in Local Linear Peters-Belson Regression |
title_full_unstemmed |
Kernel Function in Local Linear Peters-Belson Regression |
title_sort |
Kernel Function in Local Linear Peters-Belson Regression |
dc.creator.fl_str_mv |
Bolbolian Ghalibaf, Mohammad |
dc.contributor.author.spa.fl_str_mv |
Bolbolian Ghalibaf, Mohammad |
dc.subject.ddc.spa.fl_str_mv |
51 Matemáticas / Mathematics 31 Colecciones de estadística general / Statistics |
topic |
51 Matemáticas / Mathematics 31 Colecciones de estadística general / Statistics Kernel Function Local Linear Peters-Belson Regression Majority Group Minority Group Welch's Approximation. Aproximación de Welch función kernel regresión lineal local |
dc.subject.proposal.spa.fl_str_mv |
Kernel Function Local Linear Peters-Belson Regression Majority Group Minority Group Welch's Approximation. Aproximación de Welch función kernel regresión lineal local |
description |
Determining the extent of a disparity, if any, between groups of people, for example, race or gender, is of interest in many fields, including public health for medical treatment and prevention of disease or in discrimination cases concerning equal pay to estimate the pay disparities between minority and majority employees. An observed difference in the mean outcome between a majority/advantaged group (AG) and minority/disadvantaged group (DG) can be due to differences in the distribution of relevant covariates. The Peters Belson (PB) method fits a regression model with covariates to the AG to predict, for each DG member, their outcome measure as if they had been from the AG. The difference between the mean predicted and the mean observed outcomes of DG members is the (unexplained) disparity of interest. PB regression is a form of statistical matching, akin in spirit to Bhattacharya's band-width matching. In this paper we review the use of PB regression in legal cases from Hikawa et al. (2010b) Parametric and nonparametric approaches to PB regression are described and we show that in nonparametric PB regression choose a kernel function can be better resulted, i.e. by selecting the appropriate kernel function we can reduce bias and variance of estimators, also increase power of test. |
publishDate |
2018 |
dc.date.issued.spa.fl_str_mv |
2018-07-01 |
dc.date.accessioned.spa.fl_str_mv |
2019-07-03T02:13:16Z |
dc.date.available.spa.fl_str_mv |
2019-07-03T02:13:16Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.content.spa.fl_str_mv |
Text |
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http://purl.org/redcol/resource_type/ART |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
publishedVersion |
dc.identifier.issn.spa.fl_str_mv |
ISSN: 2389-8976 |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/66486 |
dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/67514/ |
identifier_str_mv |
ISSN: 2389-8976 |
url |
https://repositorio.unal.edu.co/handle/unal/66486 http://bdigital.unal.edu.co/67514/ |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.spa.fl_str_mv |
https://revistas.unal.edu.co/index.php/estad/article/view/65654 |
dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Revista Colombiana de Estadística Revista Colombiana de Estadística |
dc.relation.references.spa.fl_str_mv |
Bolbolian Ghalibaf, Mohammad (2018) Kernel Function in Local Linear Peters-Belson Regression. Revista Colombiana de Estadística, 41 (2). pp. 235-249. ISSN 2389-8976 |
dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
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Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias - Departamento de Estadística |
institution |
Universidad Nacional de Colombia |
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https://repositorio.unal.edu.co/bitstream/unal/66486/1/65654-390959-1-PB.pdf https://repositorio.unal.edu.co/bitstream/unal/66486/2/65654-390959-1-PB.pdf.jpg |
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Repositorio Institucional Universidad Nacional de Colombia |
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spelling |
Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Bolbolian Ghalibaf, Mohammad0333f80f-3125-4dfd-97f4-3a00ce2758363002019-07-03T02:13:16Z2019-07-03T02:13:16Z2018-07-01ISSN: 2389-8976https://repositorio.unal.edu.co/handle/unal/66486http://bdigital.unal.edu.co/67514/Determining the extent of a disparity, if any, between groups of people, for example, race or gender, is of interest in many fields, including public health for medical treatment and prevention of disease or in discrimination cases concerning equal pay to estimate the pay disparities between minority and majority employees. An observed difference in the mean outcome between a majority/advantaged group (AG) and minority/disadvantaged group (DG) can be due to differences in the distribution of relevant covariates. The Peters Belson (PB) method fits a regression model with covariates to the AG to predict, for each DG member, their outcome measure as if they had been from the AG. The difference between the mean predicted and the mean observed outcomes of DG members is the (unexplained) disparity of interest. PB regression is a form of statistical matching, akin in spirit to Bhattacharya's band-width matching. In this paper we review the use of PB regression in legal cases from Hikawa et al. (2010b) Parametric and nonparametric approaches to PB regression are described and we show that in nonparametric PB regression choose a kernel function can be better resulted, i.e. by selecting the appropriate kernel function we can reduce bias and variance of estimators, also increase power of test.Determinar el alcance de una disparidad, si la hubiere, entre grupos de personas, por ejemplo, raza o género, es de interés en muchos campos, incluida la salud pública para el tratamiento médico y la prevención de enfermedades o en casos de discriminación en relación con la igualdad salarial para estimar las disparidades salariales entre los empleados minoritarios y mayoritarios. La regresión de Peters Belson (PB) es una forma de coincidencia estadística, similar en espíritu a la coincidencia de ancho de banda de Bhattacharya que se propone para este propósito. En este trabajo, repasamos el uso de la regresión del PB en casos legales de Bura et al. (2012). Se describen los enfoques paramétricos y no paramétricos de la regresión del PB y demostramos que en la regresión no paramétrica del PB una función de kernel adecuada puede mejorar los resultados, es decir, seleccionando la función de kernel apropiada, podemos reducir el sesgo y la varianza de los estimadores, también aumentan el poder de las pruebas.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias - Departamento de Estadísticahttps://revistas.unal.edu.co/index.php/estad/article/view/65654Universidad Nacional de Colombia Revistas electrónicas UN Revista Colombiana de EstadísticaRevista Colombiana de EstadísticaBolbolian Ghalibaf, Mohammad (2018) Kernel Function in Local Linear Peters-Belson Regression. Revista Colombiana de Estadística, 41 (2). pp. 235-249. ISSN 2389-897651 Matemáticas / Mathematics31 Colecciones de estadística general / StatisticsKernel FunctionLocal Linear Peters-Belson RegressionMajority GroupMinority GroupWelch's Approximation.Aproximación de Welchfunción kernelregresión lineal localKernel Function in Local Linear Peters-Belson RegressionArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL65654-390959-1-PB.pdfapplication/pdf410073https://repositorio.unal.edu.co/bitstream/unal/66486/1/65654-390959-1-PB.pdfb5ca8ca3b18de586ec17d30b61ede9cfMD51THUMBNAIL65654-390959-1-PB.pdf.jpg65654-390959-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg6240https://repositorio.unal.edu.co/bitstream/unal/66486/2/65654-390959-1-PB.pdf.jpg9295e84b27a740941c131a998954bea1MD52unal/66486oai:repositorio.unal.edu.co:unal/664862023-05-25 23:02:54.57Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |