Robust testing in the logistic regression model

We are interested in testing hypotheses that concern the parameter of a logistic regression model. A robust Wald-type test based on a weighted Bianco and Yohai [ Bianco, A.M., Yohai, V.J., 1996. Robust estimation in the logistic regression model. In: H. Rieder (Ed) Robust Statistics, Data Analysis,...

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Detalles Bibliográficos
Publicado: 2009
Materias:
Asymptotic distributions
Computer intensive methods
Data analysis
Empirical studies
Lecture Notes
Logistic regression models
Logistic regressions
Monte Carlo study
New York
P-values
Robust estimation
Robust statistics
Testing hypothesis
Weight functions
Distribution functions
Estimation
Function evaluation
Logistics
Statistical tests
Regression analysis
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01679473_v53_n12_p4095_Bianco
http://hdl.handle.net/20.500.12110/paper_01679473_v53_n12_p4095_Bianco
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_01679473_v53_n12_p4095_Bianco
record_format dspace
spelling paper:paper_01679473_v53_n12_p4095_Bianco2023-06-08T15:17:08Z Robust testing in the logistic regression model Asymptotic distributions Computer intensive methods Data analysis Empirical studies Lecture Notes Logistic regression models Logistic regressions Monte Carlo study New York P-values Robust estimation Robust statistics Testing hypothesis Weight functions Distribution functions Estimation Function evaluation Logistics Statistical tests Regression analysis We are interested in testing hypotheses that concern the parameter of a logistic regression model. A robust Wald-type test based on a weighted Bianco and Yohai [ Bianco, A.M., Yohai, V.J., 1996. Robust estimation in the logistic regression model. In: H. Rieder (Ed) Robust Statistics, Data Analysis, and Computer Intensive Methods In: Lecture Notes in Statistics, vol. 109, Springer Verlag, New York, pp. 17-34] estimator, as implemented by Croux and Haesbroeck [Croux, C., Haesbroeck, G., 2003. Implementing the Bianco and Yohai estimator for logistic regression. Computational Statististics and Data Analysis 44, 273-295], is proposed. The asymptotic distribution of the test statistic is derived. We carry out an empirical study to get a further insight into the stability of the p-value. Finally, a Monte Carlo study is performed to investigate the stability of both the level and the power of the test, for different choices of the weight function. © 2009 Elsevier B.V. All rights reserved. 2009 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01679473_v53_n12_p4095_Bianco http://hdl.handle.net/20.500.12110/paper_01679473_v53_n12_p4095_Bianco
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Asymptotic distributions
Computer intensive methods
Data analysis
Empirical studies
Lecture Notes
Logistic regression models
Logistic regressions
Monte Carlo study
New York
P-values
Robust estimation
Robust statistics
Testing hypothesis
Weight functions
Distribution functions
Estimation
Function evaluation
Logistics
Statistical tests
Regression analysis
spellingShingle Asymptotic distributions
Computer intensive methods
Data analysis
Empirical studies
Lecture Notes
Logistic regression models
Logistic regressions
Monte Carlo study
New York
P-values
Robust estimation
Robust statistics
Testing hypothesis
Weight functions
Distribution functions
Estimation
Function evaluation
Logistics
Statistical tests
Regression analysis
Robust testing in the logistic regression model
topic_facet Asymptotic distributions
Computer intensive methods
Data analysis
Empirical studies
Lecture Notes
Logistic regression models
Logistic regressions
Monte Carlo study
New York
P-values
Robust estimation
Robust statistics
Testing hypothesis
Weight functions
Distribution functions
Estimation
Function evaluation
Logistics
Statistical tests
Regression analysis
description We are interested in testing hypotheses that concern the parameter of a logistic regression model. A robust Wald-type test based on a weighted Bianco and Yohai [ Bianco, A.M., Yohai, V.J., 1996. Robust estimation in the logistic regression model. In: H. Rieder (Ed) Robust Statistics, Data Analysis, and Computer Intensive Methods In: Lecture Notes in Statistics, vol. 109, Springer Verlag, New York, pp. 17-34] estimator, as implemented by Croux and Haesbroeck [Croux, C., Haesbroeck, G., 2003. Implementing the Bianco and Yohai estimator for logistic regression. Computational Statististics and Data Analysis 44, 273-295], is proposed. The asymptotic distribution of the test statistic is derived. We carry out an empirical study to get a further insight into the stability of the p-value. Finally, a Monte Carlo study is performed to investigate the stability of both the level and the power of the test, for different choices of the weight function. © 2009 Elsevier B.V. All rights reserved.
title Robust testing in the logistic regression model
title_short Robust testing in the logistic regression model
title_full Robust testing in the logistic regression model
title_fullStr Robust testing in the logistic regression model
title_full_unstemmed Robust testing in the logistic regression model
title_sort robust testing in the logistic regression model
publishDate 2009
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01679473_v53_n12_p4095_Bianco
http://hdl.handle.net/20.500.12110/paper_01679473_v53_n12_p4095_Bianco
_version_ 1768541605770297344

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