Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.

Beta regressions are commonly used with responses that assume values in the standard unit interval, such as rates, proportions and concentration indices. Hypothesis testing inferences on the model parameters are typically performed using the likelihood ratio test. It delivers accurate inferences whe...

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Autores principales:	Ana C Guedes, Francisco Cribari-Neto, Patrícia L Espinheira
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a7ba3e203e9e4cec88571deb92fac450
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spelling	oai:doaj.org-article:a7ba3e203e9e4cec88571deb92fac4502021-12-02T20:09:54ZBartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.1932-620310.1371/journal.pone.0253349https://doaj.org/article/a7ba3e203e9e4cec88571deb92fac4502021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0253349https://doaj.org/toc/1932-6203Beta regressions are commonly used with responses that assume values in the standard unit interval, such as rates, proportions and concentration indices. Hypothesis testing inferences on the model parameters are typically performed using the likelihood ratio test. It delivers accurate inferences when the sample size is large, but can otherwise lead to unreliable conclusions. It is thus important to develop alternative tests with superior finite sample behavior. We derive the Bartlett correction to the likelihood ratio test under the more general formulation of the beta regression model, i.e. under varying precision. The model contains two submodels, one for the mean response and a separate one for the precision parameter. Our interest lies in performing testing inferences on the parameters that index both submodels. We use three Bartlett-corrected likelihood ratio test statistics that are expected to yield superior performance when the sample size is small. We present Monte Carlo simulation evidence on the finite sample behavior of the Bartlett-corrected tests relative to the standard likelihood ratio test and to two improved tests that are based on an alternative approach. The numerical evidence shows that one of the Bartlett-corrected typically delivers accurate inferences even when the sample is quite small. An empirical application related to behavioral biometrics is presented and discussed.Ana C GuedesFrancisco Cribari-NetoPatrícia L EspinheiraPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 6, p e0253349 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ana C Guedes Francisco Cribari-Neto Patrícia L Espinheira Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.
description	Beta regressions are commonly used with responses that assume values in the standard unit interval, such as rates, proportions and concentration indices. Hypothesis testing inferences on the model parameters are typically performed using the likelihood ratio test. It delivers accurate inferences when the sample size is large, but can otherwise lead to unreliable conclusions. It is thus important to develop alternative tests with superior finite sample behavior. We derive the Bartlett correction to the likelihood ratio test under the more general formulation of the beta regression model, i.e. under varying precision. The model contains two submodels, one for the mean response and a separate one for the precision parameter. Our interest lies in performing testing inferences on the parameters that index both submodels. We use three Bartlett-corrected likelihood ratio test statistics that are expected to yield superior performance when the sample size is small. We present Monte Carlo simulation evidence on the finite sample behavior of the Bartlett-corrected tests relative to the standard likelihood ratio test and to two improved tests that are based on an alternative approach. The numerical evidence shows that one of the Bartlett-corrected typically delivers accurate inferences even when the sample is quite small. An empirical application related to behavioral biometrics is presented and discussed.
format	article
author	Ana C Guedes Francisco Cribari-Neto Patrícia L Espinheira
author_facet	Ana C Guedes Francisco Cribari-Neto Patrícia L Espinheira
author_sort	Ana C Guedes
title	Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.
title_short	Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.
title_full	Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.
title_fullStr	Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.
title_full_unstemmed	Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.
title_sort	bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/a7ba3e203e9e4cec88571deb92fac450
work_keys_str_mv	AT anacguedes bartlettcorrectedtestsforvaryingprecisionbetaregressionswithapplicationtoenvironmentalbiometrics AT franciscocribarineto bartlettcorrectedtestsforvaryingprecisionbetaregressionswithapplicationtoenvironmentalbiometrics AT patricialespinheira bartlettcorrectedtestsforvaryingprecisionbetaregressionswithapplicationtoenvironmentalbiometrics
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Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.

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