In an experiment to understand colon carcinogenesis, all animals were exposed to a carcinogen while half the animals were also exposed to radiation. Spatially, we measured the existence of aberrant crypt foci (ACF), namely morphologically changed colonic crypts that are known to be precursors of colon cancer development. The biological question of interest is whether the locations of these ACFs are spatially correlated: if so, this indicates that damage to the colon due to carcinogens and radiation is localized. Statistically, the data take the form of binary outcomes (corresponding to the existence of an ACF) on a regular grid. We develop score??type methods based upon the Matern and conditionally autoregression (CAR) correlation models to test for the spatial correlation in such data, while allowing for nonstationarity. Because of a technical peculiarity of the score??type test, we also develop robust versions of the method. The methods are compared to a generalization of Moran??s test for continuous outcomes, and are shown via simulation to have the potential for increased power. When applied to our data, the methods indicate the existence of spatial correlation, and hence indicate localization of damage. Assuming that there are correlations in the locations of the ACF, the questions are how great are these correlations, and whether the correlation structures di?er when an animal is exposed to radiation. To understand the extent of the correlation, we cast the problem as a spatial binary regression, where binary responses arise from an underlying Gaussian latent process. We model these marginal probabilities of ACF semiparametrically, using ?xed-knot penalized regression splines and single-index models. We ?t the models using pairwise pseudolikelihood methods. Assuming that the underlying latent process is strongly mixing, known to be the case for many Gaussian processes, we prove asymptotic normality of the methods. The penalized regression splines have penalty parameters that must converge to zero asymptotically: we derive rates for these parameters that do and do not lead to an asymptotic bias, and we derive the optimal rate of convergence for them. Finally, we apply the methods to the data from our experiment.

過去組織生態研究多半探討環境與組織死亡、創建等議題，較少從組織衰退的角度來看待仍然生存於環境中的廠商與環境的互動關係。本研究試圖瞭解企業所擁有的無形資產與企業衰退的關連，並從人力資本與社會資本理論的角度來分析，企業擁有無形資產的程度越高是否企業越不容易衰退，此外，本研究欲探討企業的人力資本與社會資本是否對環境與組織衰退的關係產生干擾效果。 本研究使用長期資料追蹤法分析資料後發現，外部環境會對企業的衰退產生影響，包含較差的經濟條件與較高的產業競爭強度都容易讓企業面臨衰退的命運。但是，當企業內所持有的人力資本與社會資本程度越高，環境對於組織衰退的影響將會減弱，此外，本研究亦發現了社會資本若干變項與企業衰退的直接效果。然而，其中若干假說出現與研究預期不一致的結果，將在論文中進行詳盡的分析。 本研究企圖處理過去較少文獻進行實證的組織衰退議題，並發現組織衰退所隱含的概念並非單純是成長的相反詞，企業在追求成長的過程中，也可能造成另一個角度的衰退跡象，亦即財務風險的增加。然而，成長與高風險亦非同時存在。透過本論文的研究結果將發現不同的人力資本與社會資本對於不同角度的組織衰退會產生不甚相同的結果。總結來說，無形資產在企業面對外部環境壓力卻必須追求生存的情況下，扮演著重要的角色。 / Most previous researches in organizational ecology field focused on the relationships between external environment, organizational death, and foundings. Organizational decline studies are relatively undeveloped, especially from the perspectives of human capital and social capital. I extend the resource-based viewpoint and dynamic capability perspective to explain the relationship between environmental pressure and organizational decline. The purpose of this study is to test the model that examines the relationship between environmental factors, human capital, social capital, and decline, and the moderating effect based on a ten-year panel data collected in Taiwan. An unbalanced panel data consists of 3,634 firm years from 399 companies in Taiwan was utilized for data analyses. Research results indicate that environmental pressure significantly influences organizational decline variables. This study also finds that the higher human capital and social capital will reduce the effect of environmental factors on decline. However, some indicators of human capital and social capital do not predict outcome variables. Contrary to expectations, some predictors represent opposite results. Although some research results do not agree with previous findings, they do contribute the knowledge and understanding of these fields.

Receiver operating characteristic (ROC) curves have been widely used in evaluation of the goodness of the diagnostic method in many study fields, such as disease diagnosis in medicine. The area under the ROC curve (AUC) naturally became one of the most used variables in gauging the goodness of the diagnosis (Mossman, Somoza 1991). Since medical diagnosis often is not dichotomous, the ROC curve and AUC need to be generalized to a multi-dimensional case. The generalization of AUC to multi-class case has been studied by many researchers in the past decade. Most recently, Nakas & Yiannoutsos (2004) considered the ordered d classes ROC analysis by only considering the sensitivities of each class. Hence, their dimension is only d. Cha (2005) considered more types of mis-classification in the ordered multiple-class case, but reduced the dimension of Ferri, at.el. from d(d-1) to 2(d-1). In this dissertation we are trying to adjust and calculate the VUS for an ordered multipleclass with Cha’s 2(d-1)-dimension method. Our methodology of finding the VUS is introduced. We present the method of adjusting and calculating VUS and their statistical inferences for the 2(d-1)-dimension. Some simulation results are included and a real example will be presented. Intellectual outcomes in pediatric brain-tumor patients were investigated in a prospective longitudinal study. The Standard-Binet Intelligence Scale-Fourth Edition (SB-IV) Standard Age Score (SAS) and Composite intelligence quotient (IQ) score are examined as cognitive outcomes in pediatric brain-tumor patients. Treatment factors, patient factors and time since diagnosis are taken into account as the risk factors. Hierarchical linear/quadratic models and Gompertz based hierarchical nonlinear growth models were applied to build linear and nonlinear longitudinal curves. We use PRESS and Volume Under the Surface (VUS) as the criterions to compare these two methods. Some model interpretations are presented in this dissertation.

<p>This study extends the existing literature on how social networks enhance the performance and sustainability of small enterprises. More specifically, the study isolates and investigates the mechanisms through which social capital helps with the growth and survival of MSMEs. The evidence presented in this study strongly suggests that an indigenous social network widely practiced in Ethiopia, the &ldquo / iqqub&rdquo / , contributes significantly to the start-up, survival and development of urban MSMEs.</p>

Maximum likelihood is an ubiquitous method used in the estimation of generalized linear mixed model (GLMM). However, the method entails computational difficulties and relies on the normality assumption for random effects. We propose a second-order least squares (SLS) estimator based on the first two marginal moments of the response variables. The proposed estimator is computationally feasible and requires less distributional assumptions than the maximum likelihood estimator. To overcome the numerical difficulties of minimizing an objective function that involves multiple integrals, a simulation-based SLS estimator is proposed. We show that the SLS estimators are consistent and asymptotically normally distributed under fairly general conditions in the framework of GLMM. Missing data is almost inevitable in longitudinal studies. Problems arise if the missing data mechanism is related to the response process. This thesis develops the proposed estimators to deal with response data missing at random by either adapting the inverse probability weight method or applying the multiple imputation approach. In practice, some of the covariates are not directly observed but are measured with error. It is well-known that simply substituting a proxy variable for the unobserved covariate in the model will generally lead to biased and inconsistent estimates. We propose the instrumental variable method for the consistent estimation of GLMM with covariate measurement error. The proposed approach does not need any parametric assumption on the distribution of the unknown covariates. This makes the method less restrictive than other methods that rely on either a parametric distribution of the covariates, or to estimate the distribution using some extra information. In the presence of data outliers, it is a concern that the SLS estimators may be vulnerable due to the second-order moments. We investigated the robustness property of the SLS estimators using their influence functions. We showed that the proposed estimators have a bounded influence function and a redescending property so they are robust to outliers. The finite sample performance and property of the SLS estimators are studied and compared with other popular estimators in the literature through simulation studies and real world data examples.

Ovarian cancer (OC) is the fifth most common cancer among women and has the highest mortality of any cancer of the female reproductive system. The majority (61%) of OC cases are diagnosed at a distant stage. Because diagnoses occur most commonly at a late-stage and prognosis for advanced disease is poor, research focusing on the development of effective OC screening methods to facilitate early detection in high-risk, asymptomatic women is fundamental in reducing OC-specific mortality. Presently, there is no screening modality proven efficacious in reducing OC-mortality. However, transvaginal ultrasonography (TVS) has shown value in early detection of OC. TVS presents with the possibility of false positive results which occur when a women receives an abnormal TVS screening test result that is deemed benign following repeat testing (about 7% of the time). The purpose of this dissertation was to evaluate the impact of false positive TVS screening test results on a variety of psychological and behavioral outcomes using mixed and trajectory statistical modeling. The three specific aims of this dissertation were to 1) compare psychological and behavioral outcomes between women receiving normal and false positive results, 2) identify characteristics of women receiving false positive results associated with increased OC-specific distress and 3) characterize distress trajectories following receipt of false positive results. Analyses included a subset of women participating in an experimental study conducted through the University of Kentucky Ovarian Cancer Screening Program. 750 women completed longitudinal assessments: 375 false positive and 375 normal results. Mixed and group-based trajectory modeling were used to evaluate the specific aims. Results suggest women receiving false positive TVS result experience increased OC-specific distress compared to women receiving normal results. Among those receiving false positives, less education, no history of an abnormal screening test result, less optimism and more social constraint were associated with increased OC-specific distress. Family history was associated with increased distress among women with monitoring informational coping styles. Three distinct trajectories characterize the trajectory of distress over a four-month study period. Although decreasing over time, a notable proportion of women experience sustained high levels of OC-specific distress.

Maximum likelihood is an ubiquitous method used in the estimation of generalized linear mixed model (GLMM). However, the method entails computational difficulties and relies on the normality assumption for random effects. We propose a second-order least squares (SLS) estimator based on the first two marginal moments of the response variables. The proposed estimator is computationally feasible and requires less distributional assumptions than the maximum likelihood estimator. To overcome the numerical difficulties of minimizing an objective function that involves multiple integrals, a simulation-based SLS estimator is proposed. We show that the SLS estimators are consistent and asymptotically normally distributed under fairly general conditions in the framework of GLMM. Missing data is almost inevitable in longitudinal studies. Problems arise if the missing data mechanism is related to the response process. This thesis develops the proposed estimators to deal with response data missing at random by either adapting the inverse probability weight method or applying the multiple imputation approach. In practice, some of the covariates are not directly observed but are measured with error. It is well-known that simply substituting a proxy variable for the unobserved covariate in the model will generally lead to biased and inconsistent estimates. We propose the instrumental variable method for the consistent estimation of GLMM with covariate measurement error. The proposed approach does not need any parametric assumption on the distribution of the unknown covariates. This makes the method less restrictive than other methods that rely on either a parametric distribution of the covariates, or to estimate the distribution using some extra information. In the presence of data outliers, it is a concern that the SLS estimators may be vulnerable due to the second-order moments. We investigated the robustness property of the SLS estimators using their influence functions. We showed that the proposed estimators have a bounded influence function and a redescending property so they are robust to outliers. The finite sample performance and property of the SLS estimators are studied and compared with other popular estimators in the literature through simulation studies and real world data examples.

Made available in DSpace on 2014-06-11T19:26:07Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-02-25Bitstream added on 2014-06-13T19:33:22Z : No. of bitstreams: 1 boligon_aa_me_jabo.pdf: 786716 bytes, checksum: 55a12f5a16a7a8f8acd0c213b48d9308 (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Foram estimados parâmetros genéticos para pesos do nascimento à idade adulta de animais da raça Nelore por meio de análises uni, bi e multicaracterísticas e modelos de regressão aleatória. Os dados utilizados são de animais nascidos de 1975 e 2002, provenientes de 8 fazendas participantes do Programa de Melhoramento Genético da Raça Nelore (PMGRN). Os pesos foram obtidos do nascimento aos 8 anos de idade. Nas análises uni, bi e multicaracterísticas foram utilizados pesos em idades padrão como nascimento, desmama, ano, sobreano e aos 2, 3 e 5 anos de idade. Também foram realizadas análises utilizando o peso mais próximo aos 4,5 anos de idade como indicativo de peso adulto, considerando uma única medida a partir de 2, 3 e 4 anos de idade ou como registros repetidos de pesos a partir dessas mesmas idades. Nas análises de regressão aleatória, foram utilizados pesos de fêmeas do nascimento aos 8 anos de idade, considerando como variáveis independentes polinômios de Legendre da idade na data da pesagem. A variância residual foi modelada por meio de classes variando de 1 a 5. Foram utilizados 8 modelos de coeficientes de regressão aleatória para os efeitos direto e materno de animal, e de ambiente permanente de animal e materno. O modelo multicaracterística, incluindo registros de pesos ao desmame e à seleção é o mais indicado para a avaliação genética de pesos pós-desmama. Em avaliações genéticas para a característica de peso adulto, o emprego de modelos de repetibilidade, considerando pesos a partir de 3 anos de idade, seria o mais adequado em relação à utilização de medida única... / Weight records of Nelore cattle from birth to mature age were analyzed using univariate, bivariate, multivariate and random regression models. Records of Nelore cattle born from 1975 to 2002, from 8 herds participating in the Nelore Cattle Breeding Program (NCBP) were used. The weights were obtained from birth to 8 years of age. Weights at birth, weaning, yearling, 18 months and 2, 3 and 5 years of age were analyzed using univariate, bivariate and multivariate models. Also, as indicative of the mature weight, the weight closest to 4.5 years of age, was analyzed considering only one record or repeated records obtained from 2, 3 and 4 years of age. For random regression models age of cow varied from birth to 8 years. Direct and maternal genetic and, animal and maternal permanent environmental variances were modeled by random regression on Legendre polynomials of age at recording, with order of fit from 3 to 6 and a total of 8 models. Residual variances were modeled by a step function with 1 or 5 classes. The multivariate model including weight records at weaning and at selection age is the most indicated for genetic evaluation of pos-weaning weights. For genetic evaluation of mature weight to use repeated records obtained from 3 years of age is better than only one record per animal. The random regression models were able to model changes of variances with age adequately, with parameter estimates similar to those obtained by multivariate analyses. The model with direct and maternal genetic effects, animal and maternal permanent environmental effects ajusted by quartic, cubic, sixth and cubic polynomials, respectively, and residual variances modeled by 5 classes, was the most adequate to describe the covariance structure of the data...(Complete abstract, click electronic access below)

Made available in DSpace on 2014-06-11T19:32:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-11-05Bitstream added on 2014-06-13T19:02:48Z : No. of bitstreams: 1 mendozasanchez_g_dr_jabo.pdf: 284774 bytes, checksum: 92c1507cf74421e8e38247e70aded393 (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Universidade Estadual Paulista (UNESP) / Considerando-se que a contagem de células somáticas (CCS) de amostras de leite é um valioso indicador da saúde do úbere de búfalas, foi desenvolvido este trabalho com o objetivo de estimar a relação existente entre a CCS e a produção de leite (PL). Foram analisadas informações de 9404 amostras de controles de CCS e PL, referentes a 2198 lactações de animais da raça Murrah com idades entre 2 e 15 anos, filhas de 187 reprodutores, que ocorreram entre os anos 1997 e 2005. Para quantificar as perdas de PL em relação à CCS, nas análises de variância para a variável PL, foram incluídos no modelo os efeitos fixos de fazenda, ordem e ano de parto e estação do parto o escore da contagem de células somáticas (ECCS) como covariável, o efeito de animal dentro da fazenda foi considerado como aleatório. Para a estimação de parâmetros genéticos para a CCS, utilizaram-se “test day models”, a média da contagem de células somáticas na lactação (CCSt270) e a produção de leite aos 270 dias (PL270); os componentes de (co) variância foram estimados usando método de máxima verossimilhança restrita. A CCS de cada mês da lactação foi considerada como uma característica distinta, em análises uni e bicaracterísticas, o modelo incluiu como efeitos aleatórios, o genético aditivo direto e de ambiente permanente e residual. Além disso, foram considerados como efeitos fixos: grupo de contemporâneos, número de controle e idade da vaca ao parto como covariável (efeito linear e quadrático). Para a CCSt nos diferentes meses, os grupos de contemporâneos foram definidos como... / Considering that the somatic cells count (SCC) of samples of milk is a valuable indicator of the health of the buffaloes’ udder, this work was developed with the objective of estimating the relationship between SCC and milk yield (MY). Information on 9404 SCC and MY controls were analyzed. Data contained 2198 lactations of Murrah animals aging between 2 and 15 years, daughters of 187 sires, from 1997 and 2005. To quantify the decreases of MY in relation to SCC, the analyses of variance for the variable MY, included in the model a random animal effect nested in farm and the fixed effects of farm, order and year of parity and season of parity, somatic cells count score (SCCE) as covariate. For estimating genetic parameters for SCC, “test day models were used. For average of somatic cells count in the lactation (SCCt270) and milk yield to 270 days (MY270); the (co) variance components were estimated using Restricted Maximum Likelihood (MTDFREML). SCCs of every month of lactation were considered as different traits in single and double trait analyses. The model included genetic additive, permanent environmental (for SCCt270 and for MY270) and residual random effects. Other fixed effects were: contemporary group; control number and age of cow at parity as a covariate (linear and quadratic effects). For CCSt, contemporary groups were defined as flock-year-month of the control, and for SCCt270 and MY270 as herd-year- season of the parity. x It was found that all effects influenced the expression of SCCE. For first parity females, no relationship between MY and SCC was found. The results indicated that the largest decreases were observed in females with more than one parity. This category... (Complete abstract click electronic access below)

Made available in DSpace on 2014-06-11T19:33:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-02-24Bitstream added on 2014-06-13T18:45:22Z : No. of bitstreams: 1 sousajunior_sc_dr_jabo.pdf: 1454758 bytes, checksum: 5d233cf3c874be7d7b3c671f43249a20 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Para o presente estudo foram utilizadas 3.202 primeiras lactações, de vacas da raça Holandesa pertencentes a quatro fazendas da região Sudeste, registradas semanalmente, com o objetivo de verificar a influência da estrutura de dados de produção de leite no decorrer da lactação, sobre os parâmetros genéticos estimados por modelos de regressão aleatória. Foram testados quatro arquivos contendo estruturas diferentes de dados. O arquivo de controles semanais (CS) contava com 122.842 controles, o arquivo mensal (CM) com 30.883 controles, o bimestral (CB) com 15.837 controles, e por fim, o arquivo de controles trimestrais (CT) continha de 12.702 controles. O modelo utilizado foi o de regressão aleatória, e como aleatórios foram considerados os efeitos genético aditivo e o de ambiente permanente de animal. A ordem das funções de covariância para estes dois efeitos foi de sexta ordem para efeito genético aditivo e de sétima ordem para o efeito de ambiente permanente, com variâncias residuais heterogêneas a estrutura de variâncias residuais foi modelada por meio de uma “step function” O modelo teve como efeito fixo os grupos de contemporâneos (GC) comuns para todos os arquivos de dados. Os GC foram compostos por fazenda, mês e ano do controle,e como co-variável a idade da vaca ao parto (regressão linear e quadrática) e o número de dias em lactação (regressão fixa para a média populacional). Todos os arquivos de dados estudados foram analisados incluindo arquivo de genealogia composto por 4.380 animais com 3202 mães e 228 touros. As estimativas de herdabilidades para produção de leite apresentaram tendências semelhantes entre os arquivos de dados analisados, com maior semelhança entre os bancos CS, CM e CB. As estimativas de herdabilidade para produção de leite no dia do controle (PLDC) do banco CT apresentou pequenas diferenças, em relação aos demais... / To this study the first 1293 Holstein dairy lactation registered weekly were used, having cows belonging to four farms in the Southeast region of Brazil, aiming verify the milk production data structure influence during lactation under genetic parameters estimated by random regression models. Four files with different data structures were tested. The week control files (CS) counted with 122,842 controls; the month files (CM), 30,883 controls; the bimestrial (CB) had 15,837 controls and finally the quarterly (CT) had 12,702 controls. It was used the random regression model and, as random, the genetic additive and the animal permanent environmental effects were considered. The covariance function to these two effects was the sixth grade to the genetic effect additive and the seventh grade to the permanent environmental effect, having heterogeneous residual variances, and the residual variance structure was modeled by a “step function”. The model had as the fixed effect the contemporaneous groups (GC) commons to all data set, GC were compounded by farm, month, and year of control. The co-variable was the cow age at birth (linear and quadratic regression) and the milking days (fixed regression to the population average). All evaluated data files presented genealogy file composed by 4,380 animals having 1,416 mothers and 228 bulls. The estimate of heritability presented tendencies similar among the analyzed data, having the higher similarity CS, CM and CB. The CT presented small differences in the estimate of heritability when compared to the others. The CB data file presented all the analyzed genetic parameters estimative with the same tendency and magnificence of the CS and CM, allowing the milk control in a CB structure, random regression model in genetic evaluations speaking. The genetic values (VG) to partial milking period production were predicted (MRA100, MRA200, MRA300 e MRA90_305) ...(Complete abstract click electronic access below)