<p>This thesis investigates the statistical properties of preliminary test estimators of linear models with normally distributed errors. Specifically, we derive exact expressions for the mean, variance and quadratic risk (i.e. the Mean Square Error) of estimators whose form are determined by the outcome of a statistical test. In the process, some new results on the moments of truncated linear or quadratic forms in normal vectors are established.</p><p>In the first paper (Paper I), we consider the estimation of the vector of regression coefficients under a model selection procedure where it is assumed that the analyst chooses between two nested linear models by some of the standard model selection criteria. This is shown to be equivalent to estimation under a preliminary test of some linear restrictions on the vector of regression coefficients. The main contribution of Paper I compared to earlier research is the generality of the form of the test statistic; we only assume it to be a quadratic form in the (translated) observation vector. Paper II paper deals with the estimation of the regression coefficients under a preliminary test for homoscedasticity of the error variances. In Paper III, we investigate the statistical properties of estimators, truncated at zero, of variance components in linear models with random effects. Paper IV establishes some new results on the moments of truncated linear and/or quadratic forms in normally distributed vectors. These results are used in Papers I-III. In Paper V we study some algebraic properties of matrices that occur in the comparison of two nested models. Specifically we derive an expression for the inertia (the number of positive, negative and zero eigenvalues) of this type of matrices.</p>

Relationships between occupational physical exposures and risks of contracting musculoskeletal disorders are still not well understood; exposure-response relationships are scarce in the musculoskeletal epidemiology literature, and many epidemiological studies, including intervention studies, fail to reach conclusive results. Insufficient exposure assessment has been pointed out as a possible explanation for this deficiency. One important aspect of assessing exposure is the selected measurement strategy; this includes issues related to the necessary number of data required to give sufficient information, and to allocation of measurement efforts, both over time and between subjects in order to achieve precise and accurate exposure estimates. These issues have been discussed mainly in the occupational hygiene literature considering chemical exposures, while the corresponding literature on biomechanical exposure is sparse. The overall aim of the present thesis was to increase knowledge on the relationship between data collection design and the resulting precision and accuracy of biomechanical exposure assessments, represented in this thesis by upper arm postures during work, data which have been shown to be relevant to disorder risk. Four papers are included in the thesis. In papers I and II, non-parametric bootstrapping was used to investigate the statistical efficiency of different strategies for distributing upper arm elevation measurements between and within working days into different numbers of measurement periods of differing durations. Paper I compared the different measurement strategies with respect to the eventual precision of estimated mean exposure level. The results showed that it was more efficient to use a higher number of shorter measurement periods spread across a working day than to use a smaller number for longer uninterrupted measurement periods, in particular if the total sample covered only a small part of the working day. Paper II evaluated sampling strategies for the purpose of determining posture variance components with respect to the accuracy and precision of the eventual variance component estimators. The paper showed that variance component estimators may be both biased and imprecise when based on sampling from small parts of working days, and that errors were larger with continuous sampling periods. The results suggest that larger posture samples than are conventionally used in ergonomics research and practice may be needed to achieve trustworthy estimates of variance components. Papers III and IV focused on method development. Paper III examined procedures for estimating statistical power when testing for a group difference in postures assessed by observation. Power determination was based either on a traditional analytical power analysis or on parametric bootstrapping, both of which accounted for methodological variance introduced by the observers to the exposure data. The study showed that repeated observations of the same video recordings may be an efficient way of increasing the power in an observation-based study, and that observations can be distributed between several observers without loss in power, provided that all observers contribute data to both of the compared groups, and that the statistical analysis model acknowledges observer variability. Paper IV discussed calibration of an inferior exposure assessment method against a superior “golden standard” method, with a particular emphasis on calibration of observed posture data against postures determined by inclinometry. The paper developed equations for bias correction of results obtained using the inferior instrument through calibration, as well as for determining the additional uncertainty of the eventual exposure value introduced through calibration. In conclusion, the results of the present thesis emphasize the importance of carefully selecting a measurement strategy on the basis of statistically well informed decisions. It is common in the literature that postural exposure is assessed from one continuous measurement collected over only a small part of a working day. In paper I, this was shown to be highly inefficient compared to spreading out the corresponding sample time across the entire working day, and the inefficiency was also obvious when assessing variance components, as shown in paper II. The thesis also shows how a well thought-out strategy for observation-based exposure assessment can reduce the effects of measurement error, both for random methodological variance (paper III) and systematic observation errors (bias) (paper IV).

Longitudinal twin data provide important information for exploring sources of variation in human traits. In statistical models for twin data, unobserved genetic and environmental factors influencing the trait are represented by latent variables. In this way, trait variation can be decomposed into genetic and environmental components. With repeated measurements on twins, latent variables can be used to describe individual trajectories, and the genetic and environmental variance components are assessed as functions of age. This thesis contributes to statistical methodology for analysing longitudinal twin data by (i) exploring the use of random change point models for modelling variance as a function of age, (ii) assessing how nonresponse in twin studies may affect estimates of genetic and environmental influences, and (iii) providing a method for hypothesis testing of genetic and environmental variance components. The random change point model, in contrast to linear and quadratic random effects models, is shown to be very flexible in capturing variability as a function of age. Approximate maximum likelihood inference through first-order linearization of the random change point model is contrasted with Bayesian inference based on Markov chain Monte Carlo simulation. In a set of simulations based on a twin model for informative nonresponse, it is demonstrated how the effect of nonresponse on estimates of genetic and environmental variance components depends on the underlying nonresponse mechanism. This thesis also reveals that the standard procedure for testing variance components is inadequate, since the null hypothesis places the variance components on the boundary of the parameter space. The asymptotic distribution of the likelihood ratio statistic for testing variance components in classical twin models is derived, resulting in a mixture of chi-square distributions. Statistical methodology is illustrated with applications to empirical data on cognitive function from a longitudinal twin study of aging.

This thesis investigates the statistical properties of preliminary test estimators of linear models with normally distributed errors. Specifically, we derive exact expressions for the mean, variance and quadratic risk (i.e. the Mean Square Error) of estimators whose form are determined by the outcome of a statistical test. In the process, some new results on the moments of truncated linear or quadratic forms in normal vectors are established. In the first paper (Paper I), we consider the estimation of the vector of regression coefficients under a model selection procedure where it is assumed that the analyst chooses between two nested linear models by some of the standard model selection criteria. This is shown to be equivalent to estimation under a preliminary test of some linear restrictions on the vector of regression coefficients. The main contribution of Paper I compared to earlier research is the generality of the form of the test statistic; we only assume it to be a quadratic form in the (translated) observation vector. Paper II paper deals with the estimation of the regression coefficients under a preliminary test for homoscedasticity of the error variances. In Paper III, we investigate the statistical properties of estimators, truncated at zero, of variance components in linear models with random effects. Paper IV establishes some new results on the moments of truncated linear and/or quadratic forms in normally distributed vectors. These results are used in Papers I-III. In Paper V we study some algebraic properties of matrices that occur in the comparison of two nested models. Specifically we derive an expression for the inertia (the number of positive, negative and zero eigenvalues) of this type of matrices.

<p>Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the&nbsp / development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.&nbsp / There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.</p>

<p>Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the&nbsp / development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.&nbsp / There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.</p>

In this thesis, estimation in simple linear regression model with one-fold nested error is studied. To estimate the fixed effect parameters, generalized least squares and maximum likelihood estimation procedures are reviewed. Moreover, Minimum Norm Quadratic Estimator (MINQE), Almost Unbiased Estimator (AUE) and Restricted Maximum Likelihood Estimator (REML) of variance of primary units are derived. Also, confidence intervals for the fixed effect parameters and the variance components are studied. Finally, the aforesaid estimation techniques and confidence intervals are applied to a real-life data and the results are presented

Submitted by MATOS MANUEL null (manuelsoaresvet@gmail.com) on 2016-04-26T17:37:57Z No. of bitstreams: 1 Dissertação_Matos .pdf: 874261 bytes, checksum: 81dba6df3e77ecf89b32f2fbdae6debf (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-04-28T18:52:16Z (GMT) No. of bitstreams: 1 manuel_m_me_dra.pdf: 874261 bytes, checksum: 81dba6df3e77ecf89b32f2fbdae6debf (MD5) / Made available in DSpace on 2016-04-28T18:52:16Z (GMT). No. of bitstreams: 1 manuel_m_me_dra.pdf: 874261 bytes, checksum: 81dba6df3e77ecf89b32f2fbdae6debf (MD5) Previous issue date: 2016-02-26 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Com vista à padronizar as análises, os programas de melhoramento genético na pecuária de corte estabelecem determinadas idades nas quais os pesos são ajustados antes de serem avaliados e no processo de seleção, as estimativas de variabilidade genética aditiva são muito importante. Neste estudo propusemos estimar parâmetros genéticos para pesos ajustados a desmama (P205), ao 1 ano (P365) e sobreano (P550), peso metabólico ajustados (PMa205), ao 1 ano (PMa365), sobreano (PMa550) e peso metabólico real (PMr205), ao 1 ano (PMr365) e sobreano (PMr550), e estimar parâmetros genéticos para índice de kleiber (IK), ganho de peso diário (GPD) para entendimento das potenciais respostas à seleção e subsidiar a elaboração de estratégias de melhoramento. Análises genéticas foram realizadas em registros de animais do arquivo de dados com 36.505 animais pertencente à ABCZ (Associação Brasileira de Criadores de Zebu) sob dois modelos distintos. O modelo 1 incluiu o efeito genético aditivo direto e residual como aleatórios, além dos efeitos fixos do grupo de contemporâneos, definido pelas variáveis: fazenda de origem do animal junto ao criador, sexo, estação de nascimento, e o ano de nascimento, para características de pesos ajustados a P365, P550, peso metabólico ajustado PMa365, PMa550, peso metabólico real PMr365, PMr550 dias, ganho de peso GP205365, ganho de pesos GP365550, índice de Kleiber IK365 e índice de Kleiber IK550 dias. O modelo 2 incluiu, o efeito genético aditivo direto, materno, ambiente permanente materno e residual como aleatórios e os incluídos no modelo 1 (fixos) para características de P205, PMa205, PMr205, GPN205 e IK205. Para estimação de parâmetros genéticos foi utilizado o método de máxima verossimilhança restrita (REML) via software Wombat. A herdabilidade variou de 0,20 a 0,25 para P205 e P550; 0,16 a 0,20 para PMr205 e PMr550 e de 0,21 a 0,21 para PMa205 e PMa550 respectivamente. As correlações genéticas entre P205 com PMr205 e P205 com PMa205 são respectivamente 0,76 e 1. Para a correlação genética entre P550 e PMr550 e P550 com PMa550 foram 0,97 e 1. A correlação genética entre P205 e P550 foi 0,72, entre PMr205 e PMr550 foi 0,54 e para PMa205 e PMa550 foi de 0,71. As correlações genéticas entre P205 com PMa205 e P365 com PMa365 foram respectivamente 1,00 e 1,00. A herdabilidade variou de 0,24 ± 0,02 a 0,22 ± 0,02 para pesos ajustados, 0,26 ± 0,06 a 0,12 ± 0,03 para IK e 0,22 a 0,15 para GPD respectivamente. As correlações entre IK 205 e K550, IK365 e IK550, IK205 e IK365, IK205 e GPN205, IK205 e GP365550, IK365 e GP205365, IK550 e GP365550, IK205 e P205, IK550 e P550 foram 0,55, 0,09, -0,06, 0,98, 0,67, 0,95, 0,98, 0,96, 0,99 e 0,63 respectivamente. O peso metabólico ajustado e peso a idade-padrão demostram semelhanças entre estimativas de parâmetros genéticos, as herdabilidade e correlações genéticas não são a mesma característica quando se trabalha com o peso a idade padrão ou peso metabólico não ajustado e O Índice de Kleiber apresenta vantagens de ser utilizado como critério de seleção nos programas de melhoramento genético / In order to standardize the analysis, breeding programs in beef cattle establish certain ages in which the weights are adjusted before being evaluated, and in the selection process, the additive genetic variability estimates are very important. In this study, proposed to estimate genetic parameters for weights adjusted weaning (W205) to one year (W365) and yearling (W550), metabolic weight adjusted weaning (AMW205) to one year (AMW365) and yearling (AMW550) and weight real metabolic weaning (RMW205) to one year (RMW365) and yearling (RMW550) to estimate genetic parameters to Kleiber index (KI), avarage daily weight gained (ADWG), for more comprehensive understanding of potential responses to selection and to support the development of the breed improvement strategies and to demonstrate the consequences of the metabolic weight value, without any correction for age on the estimation of variance components and prediction of genetic values. Genetic analyzes were conducted on animals records of the data file with 36,505 animals belonging to ABCZ (Brazilian Association of Zebu Breeders) in two different models. Model 1 included direct additive genetic effect and residual as random, besides the fixed effects of contemporary group, defined by variables: the animal farm origin with the creator, sex, birth season, and year of birth, for features of W365, W550, AMW365, AMW550, RMW365 and RMW550, weight gain of WG205365; weight gain WG365550; Kleiber index KI365 and Kleiber index to KI550. Model 2 included the direct additive genetic effect, maternal, permanent maternal environment and residual as random and the included in the model 1 (fixed) for features W205, AMW205, RMW205, average daily gained weight from birth to weaning GWB205 and index Kleiber KI205 days. To estimate genetic parameters the restricted maximum likelihood method (REML) used Wombat software. The heritability ranges from 0.20 to 0.25 for W205 and W550; 0.16 to 0.20 for RMW205 and RMW550 from 0.21 to 0.21 for AMW205 and AMW550 respectively. Genetic correlations between W205 with RMW205 and W205 WITH AMW205 are respectively 0.76 and 1. For the genetic correlation between W550 and RMW550 and W550 with AMW550 were 0.97 and 1. The genetic correlation between W205 and W550 was 0.72, between RMW205 and RMW550 was 0.54 and for AMW205 and AMW550 was 0.71. Genetic correlations between W205 with AMW205 and W365 with AMW365 are respectively 1.00 and 1.00. Heritability ranges from 0,24 ± 0.02 to 0.22 ± 0.02 for adjusted weights 0.26 ± 0.06 to 0.12 ± 0.03 and KI to 0.22 to 0.15 ADWG, respectively. Correlations between KI 205 and KI550, KI365 and KI550, KI205 and KI365, KI205 and GWB205, KI205 and WG365550, KI365 and WG205365, KI550 and WG365550, KI205 and W205, KI550 and W550 were 0.55, 0.09, -0 06, 0.98, 0.67, 0.95, 0.98, 0.96, 0.99 and 0.63 respectively. Adjusted metabolic weight and the weight at standard age demonstrate similarities between estimates of genetic parameters, heritability and genetic correlations are not the same feature when working with the weight of the standard age or unadjusted metabolic weight. Kleiber Index has advantages of being used as selection criteria in genetic improvement programs / CNPq: 190843/2013-6

Made available in DSpace on 2014-06-11T19:26:07Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-07-31Bitstream added on 2014-06-13T18:54:04Z : No. of bitstreams: 1 oliveirajunior_bc_me_jabo.pdf: 377876 bytes, checksum: 959f8b30ee240eb826bbd8afca79e17a (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / dados de prova de ganho em peso (PGP) em confinamento, visando aumento na resposta à seleção pela inclusão de informações de parentesco nas estimativas dos parâmetros genéticos, assim como na acurácia dos valores genéticos estimados e na classificação final dos animais. As características analisadas foram o peso ao final da PGP (P378), o ganho em peso após o período de adaptação (G112), um índice considerando P378 e G112 (IPGP), além do peso inicial e dois pesos intermediários. Foram utilizadas 18.825 mensurações de pesos de 4.758 animais. Os modelos de dimensão finita considerados incluíram os efeitos fixos de mês e ano de nascimento (1977 a 2006) e classe de idade da mãe ao parto (2 a ≥12 anos), além do efeito linear da idade do animal no início da PGP como covariável. Quanto aos efeitos genéticos, foram considerados dois modelos, um só com o efeito genético direto e outro incluindo o efeito de ambiente permanente materno. Os modelos de regressão aleatória incluíram, como aleatórios, os efeitos genéticos aditivos direto, de ambiente permanente direto e materno e, como fixos, os efeitos de grupo de contemporâneos, a classe de idade da vaca ao parto e o polinômio ortogonal de Legendre da idade do animal (regressão quadrática), como covariáveis. Para comparar os resultados obtidos pelos modelos de regressão aleatória, foram conduzidas análises multicaracterísticas. Um total de 13 modelos de regressão aleatória, aplicando polinômios de segunda a quinta ordem foram considerados para modelar os efeitos genéticos aditivos direto e de ambiente permanente direto e materno. O resíduo foi modelado considerando 1, 3, 4, 6 e 9 classes de variâncias. O modelo contendo 4 classes de variâncias foi o que melhor descreveu o comportamento da trajetória para o efeito... / This work was carried through with the objective of study different analysis forms of datasets regarding weight gain test (PGP) in feedlot, aiming improve in selection response through the inclusion of kinship information on estimates of genetic parameters, as well as in the estimated breeding values accuracy and in the final classification of the animals. We analyzed the characteristics weight at the end of PGP (P378), the weight gain after adaptation period (G112), an index considering P378 and G112 (IPGP), as well as the initial weight and two intermediate weights. 18,825 records of weights from 4.758 animals had been used. The considered models of finite dimension had included the fixed effects of year of birth (1977 to 2006) and cow age at birth class (2 ≥12 years), as well as the linear effect of the age of the animal at the PGP beginning as covariate. In spite the genetic analyses, we considered two models: one only with the direct genetic effect and another one including the maternal permanent environment effect. The random regression models included, as random, the additive direct genetic effect, the permanent direct and maternal environment effect, and, as fixed effects, the contemporary group, age of cow at birth class and the Legendre orthogonal polynomial of the animal age (quadratic regression), as covariates. In order to compare the achieved results for the models of random regression, we precede multicharacteristic analysis. A total of 15 models of random regression, applying polynomials of second to fifth order had been considered to fit the additive direct genetic effect and direct and maternal permanent environment effects. The residual was fitted considering 1, 3, 4, 6 and 9 variance classes. The model containing 4 variance classes was the ones that better described the trajectory... (Complete abstract click electronic access below)

Submitted by HELSI MARIA ISIDRO CRISTOBAL null (helmar2009@live.com.mx) on 2017-10-25T12:25:09Z No. of bitstreams: 1 Dissertação_Helsi_final.pdf: 975344 bytes, checksum: bb2e31aa42ebcacbcd49b7790b75ac33 (MD5) / Approved for entry into archive by Monique Sasaki (sayumi_sasaki@hotmail.com) on 2017-10-31T15:36:17Z (GMT) No. of bitstreams: 1 cristobal_hmi_me_jabo.pdf: 975344 bytes, checksum: bb2e31aa42ebcacbcd49b7790b75ac33 (MD5) / Made available in DSpace on 2017-10-31T15:36:17Z (GMT). No. of bitstreams: 1 cristobal_hmi_me_jabo.pdf: 975344 bytes, checksum: bb2e31aa42ebcacbcd49b7790b75ac33 (MD5) Previous issue date: 2017-09-26 / Consejo Nacional de Ciencia y Tecnología (CONACYT) / Os programas de melhoramento em espécies aquícolas apresentam, no geral, um número restrito de famílias e um pequeno tamanho efetivo populacional, levando ao acasalamento de animais aparentados e, consequentemente, ao aumento da endogamia. Por sua vez, maiores níveis de endogamia tendem a ocasionar queda no desempenho dos animais causada pela depressão endogâmica. O objetivo deste estudo foi estimar os níveis de endogamia e depressão endogâmica sobre as características de peso à despesca, comprimento à despesca e resistência a Piscirickettsia salmonis em uma população de salmão coho. A resistência a Piscirickettsia salmonis foi definida como o dia da morte de cada peixe após desafio conduzido em dois anos, com média de 42 dias em 2012 e 14 dias no ano de 2014. Foi utilizado um banco de dados composto por 53.504 observações, provenientes de nove gerações e 930 famílias. A estimação dos componentes de variância e endogamia foram obtidas utilizando o programa computacional AIREMLF90 e os valores de depressão endogâmica foram estimados a partir de um modelo animal. Os valores observados para o coeficiente de endogamia foram crescentes ao longo das gerações, com uma taxa média máxima de 8,75% no ano de 2014. A depressão endogâmica afetou em maior nível as características de peso à despesca e dia de morte, com redução de 6,4 e 9,2% no desempenho dos animais, respectivamente, para o nível máximo de endogamia observado (30%). Os resultados indicam a necessidade de uso de estratégias mais efetivas de controle da endogamia para a manutenção do progresso genético do programa de melhoramento de salmão coho. / Aquaculture breeding programs present, in general, low number of families and reduced effective population size, resulting in mating of related animals and, consequently, increased level of inbreeding. High inbreeding coefficient may negatively impact the animals’ performance due to inbreeding depression. The objective of this study was to estimate inbreeding coefficient and inbreeding depression on growth traits and resistance against Piscirickettsia salmonis in a coho salmon population. Resistance against P. salmonis was defined as days to death of each fish after being challenged in two different years, with an average of 42 days in 2012 and 14 days in 2014. Data of 53,504 animals from 930 families was analyzed. Variance components were estimated using the software AIREMLF90, and inbreeding depression was estimated under an animal model. An increasing rate of inbreeding was observed, attaining an average of 8.75% in 2014. Inbreeding depression was more pronounced for harvest weight (PD) and days to death (DM), in comparison with harvest length. At the highest observed inbreeding level (30%), the estimated reduction caused by inbreeding depression was equal to 6,4% for PD and 9,2% for DM. The results indicate the necessity to control inbreeding more effectively for the studied coho salmon population, to guarantee genetic progress in the long term. / CONACYT: 579741/410470