Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais

Detalhes bibliográficos
Autor(a) principal: Resende, Luiz Fernando Silva
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/36951
Resumo: When bee experiments are conducted in laboratories, the interested features are analyzed in groups of caged bees, and typically, the mortality is evaluated considering specific periods of time. Therefore, since all the data is censored, the exact period of the interested feature is unknown. This happens because bees are insects that live in society, and in order to avoid any physiologic and behavioral changes, they should always be kept in groups. Thus, statistical techniques are required for survival analys is, consisting in a set of methods for data evaluation in which the variable is the time until the occurrence of some event of interest. The death of an individual inside the cage could affect all the other bees, leading to correlated observations. The parametric models in survival analysis are useful when the distribution until the event is supposedly known, and the best -known models are: the exponential, Weibull, lognormal and the Cox semiparametric model, with the latter being robust and flexible in several contexts, such as stratification, time dependent variables and multiple events. In the first part of this research, it was performed the analysis of experiments considering data from Trigona spinipes bees, with two routes of intoxication using the natural Neem repellent: by contact (spray) or oral (ingestion). The data from the experiment were collected at every 12 hours, having the time until the occurrence of bee death as variable and the method of how the repellent was applied as covariate. Non-parametric analysis was performed, adjusting the parametric model of Weibull and a semiparametric technique by proportional models of Cox, using the IceReg package in R. It can be stated that the repellent ingestions causes less damage to T. spinipes than the contact (or spraying) of it, especially in the first 288 hours, with the best adjustments being the semiparametric model. It was concluded that the most significant route for bee intoxication was the way that the repellent was applied; the highest mortalit y was caused by spraying. Thus, it is recommended that the product application time should differ from the foraging time of T. spinipes. In the second part of this research some variations of the Cox model were studied over time for recurrent events in bio-essay data of oral toxicity in Africanized bees. Survival studies using Africanized bees almost never consider proportions of mortalities within experimental units. This is relevant due to the hygienic behavior of this species. The death of each bee created an event of interest and its time interval was recorded. The classic Cox models and their adaptations for recurrent events denominated AG, LWA, GT- UR, PWP-CP, PWP-GT and TT-R were considered. In order to select the model that best fits the data, it was used: the Wald test, the verisimilitude ratio, Logrank, and the AIC information criteria. Moreover, for the basic risk analysis for the use of the Cox regression model, techniques of graphical analysis of accumulated risk - Schoenfeld Residual, Martingale Residual and Deviance Residual - were used. The stratified models, which consider the dependence of the proportion of mortality on Africanized Bees inside the cage, were higher than those that were not stratified, being the The PWP-CP model, with a Counting Process type interval, the best fit.
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spelling Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriaisModels for recurrent events related to the measurement of bee mortality influences in laboratory experimentsAbelhas - MortalidadeRisco basalTrigona spinipesModelo de regressão de CoxBees - MortalityHazardCox regression modelEstatísticaWhen bee experiments are conducted in laboratories, the interested features are analyzed in groups of caged bees, and typically, the mortality is evaluated considering specific periods of time. Therefore, since all the data is censored, the exact period of the interested feature is unknown. This happens because bees are insects that live in society, and in order to avoid any physiologic and behavioral changes, they should always be kept in groups. Thus, statistical techniques are required for survival analys is, consisting in a set of methods for data evaluation in which the variable is the time until the occurrence of some event of interest. The death of an individual inside the cage could affect all the other bees, leading to correlated observations. The parametric models in survival analysis are useful when the distribution until the event is supposedly known, and the best -known models are: the exponential, Weibull, lognormal and the Cox semiparametric model, with the latter being robust and flexible in several contexts, such as stratification, time dependent variables and multiple events. In the first part of this research, it was performed the analysis of experiments considering data from Trigona spinipes bees, with two routes of intoxication using the natural Neem repellent: by contact (spray) or oral (ingestion). The data from the experiment were collected at every 12 hours, having the time until the occurrence of bee death as variable and the method of how the repellent was applied as covariate. Non-parametric analysis was performed, adjusting the parametric model of Weibull and a semiparametric technique by proportional models of Cox, using the IceReg package in R. It can be stated that the repellent ingestions causes less damage to T. spinipes than the contact (or spraying) of it, especially in the first 288 hours, with the best adjustments being the semiparametric model. It was concluded that the most significant route for bee intoxication was the way that the repellent was applied; the highest mortalit y was caused by spraying. Thus, it is recommended that the product application time should differ from the foraging time of T. spinipes. In the second part of this research some variations of the Cox model were studied over time for recurrent events in bio-essay data of oral toxicity in Africanized bees. Survival studies using Africanized bees almost never consider proportions of mortalities within experimental units. This is relevant due to the hygienic behavior of this species. The death of each bee created an event of interest and its time interval was recorded. The classic Cox models and their adaptations for recurrent events denominated AG, LWA, GT- UR, PWP-CP, PWP-GT and TT-R were considered. In order to select the model that best fits the data, it was used: the Wald test, the verisimilitude ratio, Logrank, and the AIC information criteria. Moreover, for the basic risk analysis for the use of the Cox regression model, techniques of graphical analysis of accumulated risk - Schoenfeld Residual, Martingale Residual and Deviance Residual - were used. The stratified models, which consider the dependence of the proportion of mortality on Africanized Bees inside the cage, were higher than those that were not stratified, being the The PWP-CP model, with a Counting Process type interval, the best fit.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Ao se realizar experimentos com abelhas em laboratórios, as características de interesse são analisadas em grupos de abelhas confinadas em gaiolas, por se tratar de insetos que vivem em sociedade e, para evitar alterações fisiológicas e comportamentais, devem ser mantidos sempre em grupo. Normalmente, se avalia a mortalidade em intervalos de tempo pré-determinados. Assim, os dados obtidos são censurados, ou seja, não se conhece o tempo exato de ocorrência da característica de interesse. Então, se faz necessária a utilização de técnicas estatísticas de análise de sobrevivência, que consiste em um conjunto de métodos para a avaliação de dados em que a variável resposta é o tempo, até a ocorrência de algum evento de interesse. Além disso, a mortalidade de uma abelha ocorrida dentro da gaiola pode afetar os outros indivíduos. Assim, teríamos observações correlacionadas. Os modelos paramétricos em análise de sobrevivência são úteis quando a distribuição até o evento é supostamente conhecida, e os modelos mais conhecidos são o exponencial, Weibull, log-normal. Já o modelo semiparamétrico de Cox é robusto e flexível em diversos contextos, como estratificação, variáveis dependentes do tempo, eventos múltiplos. Na primeira parte deste trabalho , realizou-se a análise de experimento considerando dados de abelhas Trigona spinipes submetidas a duas vias de intoxicação do repelente natural Neem: por contato (pulverização) ou oral (ingestão). Os dados foram coletados a cada 12 horas, sendo a variável resposta o tempo até a ocorrência da morte da abelha e o método de aplicação do repelente considerado como covariável. Foi realizada a analise nã o paramétrica, o ajuste pelo modelo paramétrico de Weibull e a técnica semiparamétrica por modelos proporcionais de Cox utilizando o pacote icenReg no R. Pode-se dizer que a ingestão do repelente causa menor dano às abelhas-irapuá do que a pulverização do mesmo, principalmente nas primeiras 288 horas, com o melhor ajuste sendo o semiparamétrico. Concluiu-se que a via de intoxicação das abelhas, ou seja, a forma de aplicação do repelente é o fator de maior significância, sendo a pulverização a via de intoxicação que causa mortalidade. Assim, recomenda-se que o horário de aplicação do produto seja diferente do horário de forrageamento da Trigona spinipes. Na segunda parte deste trabalho, estudou-se algumas variações do modelo de Cox para eventos recorrentes em dados de bioensaio de toxicidade oral, ao longo do tempo, com abelhas africanizadas. Em estudos de sobrevivência em abelhas africanizadas raramente são considera- das as proporções de mortalidade, dentro das unidades experimentais, nos ajustes dos modelos. Isso é importante, em razão das características de comportamento higiênico destas. A morte de cada abelha constituiu o evento de interesse e o seu intervalo de tempo foi registrado. Foram considerados os modelos clássicos de Cox e suas adaptações para eventos recorrentes denominadas AG, LWA, GT-UR, PWP-CP, PWP-GT e TTR. Para selecionar o modelo que melhor se ajuste aos dados, foram utilizados os testes de Wald, da razão de verossimilhança, Logrank e o critério de informação de AIC. Para avaliar a suposição básica de riscos proporcionais para o uso do modelo de regressão de Cox, foram utilizadas técnicas de análise gráfica do risco acumulado, dos Resíduos de Schoenfeld, dos Resíduos de Martingale e Resíduo Deviance. Os modelos estratificados que consideram a dependência da proporção de mortalidade em abelhas africanizadas dentro da gaiola mostraramse superiores aos não estratificados, sendo o modelo PWP-CP, com intervalo do tipo Counting Process, o que apresentou melhor ajuste.Universidade Federal de LavrasPrograma de Pós-Graduação em Estatística e Experimentação AgropecuáriaUFLAbrasilDepartamento de EstatísticaBrighenti, Carla Regina GuimarãesGuimarães, Paulo Henrique SalesCarvalho, Stephan MalfitanoGiarola, Luciane Teixeira PassosResende, Luiz Fernando Silva2019-09-26T13:20:29Z2019-09-26T13:20:29Z2019-08-272019-06-25info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfRESENDE, L. F. S. Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais. 2019. 80 p. Dissertação (Mestrado em Estatística) – Universidade Federal de Lavras, Lavras, 2019.http://repositorio.ufla.br/jspui/handle/1/36951porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLA2019-09-26T13:20:29Zoai:localhost:1/36951Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2019-09-26T13:20:29Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
Models for recurrent events related to the measurement of bee mortality influences in laboratory experiments
title Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
spellingShingle Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
Resende, Luiz Fernando Silva
Abelhas - Mortalidade
Risco basal
Trigona spinipes
Modelo de regressão de Cox
Bees - Mortality
Hazard
Cox regression model
Estatística
title_short Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
title_full Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
title_fullStr Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
title_full_unstemmed Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
title_sort Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais
author Resende, Luiz Fernando Silva
author_facet Resende, Luiz Fernando Silva
author_role author
dc.contributor.none.fl_str_mv Brighenti, Carla Regina Guimarães
Guimarães, Paulo Henrique Sales
Carvalho, Stephan Malfitano
Giarola, Luciane Teixeira Passos
dc.contributor.author.fl_str_mv Resende, Luiz Fernando Silva
dc.subject.por.fl_str_mv Abelhas - Mortalidade
Risco basal
Trigona spinipes
Modelo de regressão de Cox
Bees - Mortality
Hazard
Cox regression model
Estatística
topic Abelhas - Mortalidade
Risco basal
Trigona spinipes
Modelo de regressão de Cox
Bees - Mortality
Hazard
Cox regression model
Estatística
description When bee experiments are conducted in laboratories, the interested features are analyzed in groups of caged bees, and typically, the mortality is evaluated considering specific periods of time. Therefore, since all the data is censored, the exact period of the interested feature is unknown. This happens because bees are insects that live in society, and in order to avoid any physiologic and behavioral changes, they should always be kept in groups. Thus, statistical techniques are required for survival analys is, consisting in a set of methods for data evaluation in which the variable is the time until the occurrence of some event of interest. The death of an individual inside the cage could affect all the other bees, leading to correlated observations. The parametric models in survival analysis are useful when the distribution until the event is supposedly known, and the best -known models are: the exponential, Weibull, lognormal and the Cox semiparametric model, with the latter being robust and flexible in several contexts, such as stratification, time dependent variables and multiple events. In the first part of this research, it was performed the analysis of experiments considering data from Trigona spinipes bees, with two routes of intoxication using the natural Neem repellent: by contact (spray) or oral (ingestion). The data from the experiment were collected at every 12 hours, having the time until the occurrence of bee death as variable and the method of how the repellent was applied as covariate. Non-parametric analysis was performed, adjusting the parametric model of Weibull and a semiparametric technique by proportional models of Cox, using the IceReg package in R. It can be stated that the repellent ingestions causes less damage to T. spinipes than the contact (or spraying) of it, especially in the first 288 hours, with the best adjustments being the semiparametric model. It was concluded that the most significant route for bee intoxication was the way that the repellent was applied; the highest mortalit y was caused by spraying. Thus, it is recommended that the product application time should differ from the foraging time of T. spinipes. In the second part of this research some variations of the Cox model were studied over time for recurrent events in bio-essay data of oral toxicity in Africanized bees. Survival studies using Africanized bees almost never consider proportions of mortalities within experimental units. This is relevant due to the hygienic behavior of this species. The death of each bee created an event of interest and its time interval was recorded. The classic Cox models and their adaptations for recurrent events denominated AG, LWA, GT- UR, PWP-CP, PWP-GT and TT-R were considered. In order to select the model that best fits the data, it was used: the Wald test, the verisimilitude ratio, Logrank, and the AIC information criteria. Moreover, for the basic risk analysis for the use of the Cox regression model, techniques of graphical analysis of accumulated risk - Schoenfeld Residual, Martingale Residual and Deviance Residual - were used. The stratified models, which consider the dependence of the proportion of mortality on Africanized Bees inside the cage, were higher than those that were not stratified, being the The PWP-CP model, with a Counting Process type interval, the best fit.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-26T13:20:29Z
2019-09-26T13:20:29Z
2019-08-27
2019-06-25
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv RESENDE, L. F. S. Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais. 2019. 80 p. Dissertação (Mestrado em Estatística) – Universidade Federal de Lavras, Lavras, 2019.
http://repositorio.ufla.br/jspui/handle/1/36951
identifier_str_mv RESENDE, L. F. S. Modelos para eventos recorrentes na mensuração da influência da mortalidade entre abelhas em experimentos laboratoriais. 2019. 80 p. Dissertação (Mestrado em Estatística) – Universidade Federal de Lavras, Lavras, 2019.
url http://repositorio.ufla.br/jspui/handle/1/36951
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language por
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
Programa de Pós-Graduação em Estatística e Experimentação Agropecuária
UFLA
brasil
Departamento de Estatística
publisher.none.fl_str_mv Universidade Federal de Lavras
Programa de Pós-Graduação em Estatística e Experimentação Agropecuária
UFLA
brasil
Departamento de Estatística
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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