Cystic fibrosis (CF) is the most common life-restricting, genetically inherited disease among Caucasians affecting approximately 30,000 people in the United States. Lung disease is the major cause of morbidity and mortality in CF. A number of oral, inhaled, and intravenous therapies are available to combat CF lung disease. Of these, this research project focused on inhaled dornase alfa, oral azithromycin, inhaled tobramycin, and inhaled aztreonam. Data to address three research aims were requested and obtained from the Cystic Fibrosis Foundation Patient Registry (CFFPR). The first aim examined the use of inhaled dornase alfa in younger children with CF. With no clinical efficacy data of dornase alfa in children ≤ 6 years of age, the study utilized subsequent forced expiratory volume in 1 second (FEV₁) measured between 6 - 7 years of age, to assess the effectiveness of long-term dornase alfa use ≤ 6 years of age. Propensity score methods were used to reduce the likelihood of treatment indication bias. The results suggested that receiving treatment with dornase alfa before 6 years of age did not improve FEV₁ between 6 - 7 years. Unmeasured covariates leading to treatment indication bias were likely one of the key explanations for these results. Additionally, lack of a more sensitive outcome than FEV₁ to assess lung function in young patients with early lung damage was thought to be another reason for the failure to reject the null hypothesis. The second aim assessed the long-term clinical effectiveness of chronic azithromycin use on the rate of FEV₁ decline in CF patients between 6 - 20 years of age. This study was novel in that the rate of FEV₁ decline, rather than change in FEV₁ from baseline, was the primary outcome, which was characterized using propensity score matching followed by a linear mixed model analysis. The results of the analysis suggested that the rate of FEV₁ decline was slower in patients who did not receive chronic treatment with azithromycin. Treatment indication bias was thought to play an important role in the direction of the association between treatment and outcome. Associations between FEV₁ % predicted and many of the other study variables included in the analysis were consistent with previous studies. The final aim compared the clinical effectiveness of a combination of inhaled tobramycin and aztreonam with inhaled tobramycin alone on the rate of FEV₁ decline in CF patients between 6 - 20 years of age. This aim was novel in that the effect of this combination treatment on rate of decline in FEV₁ has never been assessed. A linear mixed model analysis was used after matching patients in the two treatment groups on their propensity scores. Once again, the results were contrary to the alternative hypothesis with the combination group having a steeper rate of FEV₁ decline than the group that was treated with tobramycin alone. An important reason for this result was thought to be unresolved treatment indication bias that could not be eliminated even with the use of the propensity score methods used to test the associated hypothesis. The use of validated methods of analysis, i.e., propensity scores, to counter treatment indication bias using the largest available observational dataset for CF, was one of the key strengths of this study. Moreover, this study highlighted important weaknesses in the CFFPR with regards to lack of data on patient and physician-level variables - an area of active interest for the Cystic Fibrosis Foundation.

Background: By 2050, it is estimated that 14 million older Americans will live with Alzheimer’s disease (AD), a progressive form of dementia with unknown cause or cure. Persons with AD and related dementias (ADRD) become increasingly dependent on others as they experience cognitive decline, which concomitantly undermines individuals’ functional skills, social initiative, and quality of life. The Alzheimer’s Association advocates for interventions that address cognition, mood, behavior, social engagement, and by extension, quality of life – goals music therapists often address. Although a small but growing body of literature suggests that clinical music therapy may be effective, the evidentiary support for the use and appropriate application of music as a form of treatment with this population is currently limited. Objectives: This thesis consisted of the development of a Clinical Practice Model of music therapy for persons with ADRD. It also examined the effectiveness of a specific, protocol-based music therapy intervention, grounded in this model, relative to a verbal discussion activity. Methods: The Clinical Practice Model is theoretically grounded in the biopsychosocial model of healthcare (Engel, 1980) and Kitwood’s (1997) personhood framework, and I developed it through extensive literature review and expert input. It includes an organizational schema for applying intervention strategies, per six themes: cognition, attention, familiarity, audibility, structure, and autonomy. The initial model predicts that an intervention built upon this schema will influence social-affective responses, quality of life, and in turn, psychosocial symptoms of ADRD. I tested a singing-based music therapy intervention, grounded in this model, through a randomized clinical crossover trial. I compared participants’ responses to music therapy to a non-music verbal discussion activity, and both conditions followed a protocol. Dependent variables included: (1) affective responses (self-reported feelings, observed emotions, and observed mood), (2) social engagement, and (3) observed quality of life. Thirty-two individuals with ADRD (n = 6 men, n = 26 women) ages 65-97 years old (μ̂ = 84.13) participated in this study. I randomly assigned treatment order; each treatment occurred in small-group format, three times per week in the afternoon (25 minutes each session), for two consecutive weeks. A two-week “wash-out” period occurred between conditions. Credentialed music therapists led both study conditions. This study followed recommendations from the National Institutes of Health Behavior Change Consortium (Bellg et al., 2004) to enhance quality assurance in protocol administration and data collection. Results and Significance: I used a linear mixed model approach to analysis. Music therapy exacted a significant, positive effect on self-reported feelings, observed emotions, and constructive engagement, particularly for individuals with moderate dementia. Results also suggested that men’s feelings improved in response to music therapy only, whereas women responded positively to both conditions. Weekly observations failed to indicate a significant change in mood or quality of life across the eight-week study. Based on these findings, I revised the Clinical Practice Model to include wellbeing (an outcome more concordant with psychosocial change in response to music intervention) rather than global quality of life (affected by numerous aspects of the care milieu). In addition to the Clinical Practice Model to the music therapy profession, contributions of this thesis include a rigorous clinical study and practical implications for music therapy practice, including the importance of considering patient characteristics and careful selection and implementation of music in a music therapy intervention.

A semiparametric proportional likelihood ratio model was proposed by Luo and Tsai (2012) which is suitable for modeling a nonlinear monotonic relationship between the response variable and a covariate. Extending the generalized linear model, this model leaves the probability distribution unspecified but estimates it from the data. In this thesis, we propose to extend this model into analyzing the longitudinal data by incorporating random effects into the linear predictor. By using this model as the conditional density of the response variable given the random effects, we present a maximum likelihood approach for model estimation and inference. Two numerical estimation procedures were developed for response variables with finite support, one based on the Newton-Raphson algorithm and the other one based on generalized expectation maximization (GEM) algorithm. In both estimation procedures, Gauss-Hermite quadrature is employed to approximate the integrals. Upon convergence, the observed information matrix is estimated through the second-order numerical differentiation of the log likelihood function. Asymptotic properties of the maximum likelihood estimator are established under certain regularity conditions and simulation studies are conducted to assess its finite sample properties and compare the proposed model to the generalized linear mixed model. The proposed method is illustrated in an analysis of data from a multi-site observational study of prodromal Huntington's disease.

Although the captive reproduction of non-avian reptiles has increased steadily since the 1970’s, a dearth of information exists on successful management practices for large captive populations of these species. The data reported here come from a captive population of ball pythons (Python regius) maintained by a commercial breeding company, The Snake Keeper, Inc. (Spanish Fork, UT). Reproductive data are available for 6,480 eggs from 937 ball python clutches. The data presented suggest that proper management practices should include the use of palpation and/or ultrasound to ensure breeding occurs during the proper time of the female reproductive cycle, and that maintenance of proper humidity during the incubation of eggs is vitally important. Ball python reproduction traits (clutch size, clutch mass, relative clutch mass, egg mass, hatch rate, egg length, egg width, hatchling mass, healthy offspring per clutch, week laid, and days of incubation) were recorded for the clutches laid during this study. For the 937 clutches, the identity of the dam and sire were known for 862 (92%) and 777 (83%) of the clutches, respectively. A multivariate model that included nine of the 11 traits listed above was compiled. Heritability and genetic and phenotypic correlations were calculated from the multivariate analysis. The trait that showed the most promise for use in artificial selection to increase reproduction rates was clutch size due to considerable genetic variation, high heritability, and favorable genetic correlations with other reproduction traits. Although large datasets have been published for twinning in avian species, relatively few are available for non-avian reptiles. Reported here are 14 sets of twins produced from 6,480 eggs from 937 ball python clutches. The survival rate for twins during the first 3 months of life in our study was 97%. Interestingly, 11 of the sets of twins were identical in sex and phenotype, and additional genetic data suggested the rate of monozygotic twinning within this captive population of ball pythons was higher than that of dizygotic twinning. Further, using microsatellite analysis we were able to generate data that shows three sets of python twins were genetically identical.

Linear mixed models (LMMs) provide a still underused methodological perspective on combining experimental and individual-differences research. Here we illustrate this approach with two-rectangle cueing in visual attention (Egly et al., 1994). We replicated previous experimental cue-validity effects relating to a spatial shift of attention within an object (spatial effect), to attention switch between objects (object effect), and to the attraction of attention toward the display centroid (attraction effect), also taking into account the design-inherent imbalance of valid and other trials. We simultaneously estimated variance/covariance components of subject-related random effects for these spatial, object, and attraction effects in addition to their mean reaction times (RTs). The spatial effect showed a strong positive correlation with mean RT and a strong negative correlation with the attraction effect. The analysis of individual differences suggests that slow subjects engage attention more strongly at the cued location than fast subjects. We compare this joint LMM analysis of experimental effects and associated subject-related variances and correlations with two frequently used alternative statistical procedures

This research paper creates a comprehensive statistical model, relating financial impact of risk engineering activity, and insurance claims costs. Specifically, the model shows important statistical relationships among six variables including: types of risk engineering activity, risk engineering dollar cost, duration of risk engineering service, and type of customer by industry classification, dollar premium amounts, and dollar claims costs. We accomplish this by using a large data sample of approximately 15,000 customer-years of insurance coverage, and risk engineering activity. Data sample is from an international casualty/property insurance company and covers four years of operations, 2006-2009. The choice of statistical model is the linear mixed model, as presented in SAS 9.2 software. This method provides essential capabilities, including the flexibility to work with data having missing values, and the ability to reveal time-dependent statistical associations.

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Linear mixed models and generalized linear mixed models are random-effects models widely applied to analyze clustered or hierarchical data. Generally, random effects are often assumed to be normally distributed in the context of mixed models. However, in the mixed-effects logistic model, the violation of the assumption of normally distributed random effects may result in inconsistency for estimates of some fixed effects and the variance component of random effects when the variance of the random-effects distribution is large. On the other hand, summary statistics used for assessing goodness of fit in the ordinary logistic regression models may not be directly applicable to the mixed-effects logistic models. In this dissertation, we present our investigations of two independent studies related to goodness-of-fit tests in generalized linear mixed models. First, we consider a semi-nonparametric density representation for the random effects distribution and provide a formal statistical test for testing normality of the random-effects distribution in the mixed-effects logistic models. We obtain estimates of parameters by using a non-likelihood-based estimation procedure. Additionally, we not only evaluate the type I error rate of the proposed test statistic through asymptotic results, but also carry out a bootstrap hypothesis testing procedure to control the inflation of the type I error rate and to study the power performance of the proposed test statistic. Further, the methodology is illustrated by revisiting a case study in mental health. Second, to improve assessment of the model fit in the mixed-effects logistic models, we apply the nonparametric local polynomial smoothed residuals over within-cluster continuous covariates to the unweighted sum of squares statistic for assessing the goodness-of-fit of the logistic multilevel models. We perform a simulation study to evaluate the type I error rate and the power performance for detecting a missing quadratic or interaction term of fixed effects using the kernel smoothed unweighted sum of squares statistic based on the local polynomial smoothed residuals over x-space. We also use a real data set in clinical trials to illustrate this application.

Made available in DSpace on 2014-06-11T19:26:09Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-11-23Bitstream added on 2014-06-13T20:14:45Z : No. of bitstreams: 1 scarpinati_ea_me_jabo.pdf: 586713 bytes, checksum: b4b8edef17de98899f05cf5fb4df2966 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Foram instalados três testes clonais de Eucalyptus spp em delineamentos de blocos completos ao acaso em diferentes tamanhos de parcelas experimentais, com 18 tratamentos (18 clones) repetidos em cada experimento. Experimento 1:-Teste clonal em delineamento de blocos ao acaso, com 6 repetições de parcelas retangulares com 42 plantas (6 linhas x 7 plantas); Experimento 2:-Teste clonal em delineamento de blocos ao acaso, com 6 repetições de parcelas lineares de 10 plantas; Experimento 3:-Teste clonal em delineamento de blocos ao acaso, com uma planta por parcela (single tree plot - STP), com 20 repetições (blocos). Aos três anos de idade foi calculado o IMA (incremento médio anual de volume). Os dados do IMA foram avaliados para os valores genotípicos e os componentes de variância para os três delineamentos através de duas metodologias de análise: a) tradicional (ANOVA) e b) modelo misto (REML/BLUP). As estimativas de interesse foram obtidas utilizando os procedimentos GLM e MIXED do software estatístico SAS (2004). Foi efetuada análise de covariância para correção do efeito de competição testando três covariáveis: índice de Heigy, Falha, Média, para os três experimentos e nas duas metodologias de análise. A metodologia REML/BLUP, foi ligeiramente superior à metodologia GLM, em todas as análises. O índice de HEIGY não foi eficiente em nenhuma metodologia de análise para os três experimentos estudados para a característica IMA aos 3 anos de idade. As covariáveis Falha e Média não melhoraram as análises no experimento de parcelas retangulares, mas contribuíram para uma melhora sutil nos experimentos em linha e de planta única. Houve alteração no ordenamento dos genótipos de um delineamento para outro em todas as metodologias de análise. A alocompetição foi a grande causadora de erro experimental entre parcelas... / Three Eucalyptus spp cloning tests were designed in plots at randomized blocks, under different arrays and experimental parcels size, having 18 treatments (18 clones), replicated in each experiment. Experiment 1: Clonal test in randomized blocks with 6 replications in rectangular parcels with 42 plants (6 lines x 7 plants); Experiment 2: Clonal test in randomized blocks, with 6 replications in linear parcels having 10 plants; Experiment 3: Clonal test in randomized blocks in Single Tree Plot – STP, having 20 replications (blocks). After three years, the average of volume annual increment – IMA was calculated. IMA data were evaluated to genotypes value and the variance components to the three designs trough two analysis methodologies: a) Traditional (ANOVA) and b) mixed model (REML/BLUP). Interested estimative were obtained using GLM and MIXED procedures from SAS (2004). Covariance analysis was done to correct the competition effect testing three covaries: Heigy index, Falha, Mean, to the three experiments and in the two analysis methodology. The REML/BLUP methodology was slightly better than GLM methodology in all analysis. The HEIGH index was not apply to none of the three evaluated methodology to IMA characteristic after three years. The Falha 8 and Mean 8 covaries did not improve the design analysis of rectangular parcels, but they contributed to a subtle improve in the line and only plant designs. There was alteration from a design genotype order to other in all analysis methodology. The alocompetition was the main responsible of experimental error between parcels. The rectangular experiment was more efficient than STP, being this one more efficient than the linear parcels to the actual commercial crop system (mono clonal planting). The STP experiment presented higher medium experimental productivity as well higher averages predicted in almost all genotypes tested ...(Complete abstract, click electronic access below)

Made available in DSpace on 2014-06-11T19:31:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-11-16Bitstream added on 2014-06-13T21:02:57Z : No. of bitstreams: 1 barbosa_l_dr_botfca.pdf: 2587351 bytes, checksum: 76e343f1e0edbbbee5cb996188d8efd2 (MD5) / É bastante comum na área agrícola, experimentos cujas variáveis respostas são contagens ou proporções. Para esse tipo de dados, utiliza-se a metodologia de modelos lineares generalizados quando as respostas são independentes. Por outro lado, quando as respostas são dependentes, há uma correlação entre as observações e isso tem que ser levado em consideração na análise, para evitar inferências incorretas sobre os coeficientes de regressão. Na literatura há técnicas disponíveis para a modelagem e análise desses dados, sendo os modelos disponíveis extensões dos modelos lineares generalizados. No presente trabalho, utiliza-se a metodologia de equação de estimação generalizada, que inclui no modelo uma matriz de correlação para a obtenção de um melhor ajuste. Outra alternativa, também abordada neste trabalho, é a utilização de um modelo linear generalizado misto, no qual o uso de efeitos aleatórios também introduz uma correlação entre observações que tenham algum efeito em comum. Essas duas metodologias são aplicadas a um conjunto de dados obtidos de um experimento para avaliar certas condições na germinação de sementes de mamona da cultivar AL Guarany 2002, com o objetivo de se verificar qual o melhor modelo de estimação para esses dados / Experiments whose response variables are counts or proportions are very common in agriculture. For this type of data, if the observational units are independent, the methodology of generalized linear models can be appropriate. On the other hand, when responses are dependent or clustered, there is a correlation between the observations and that has to be taken into consideration in the analysis to avoid incorrect inferences about the regression coefficients. In the literature there are techniques available for modeling and analyzing such type data, the models being extensions of generalized linear models. The present study explores the use of: 1) generalized estimation equations, that includes a correlation matrix to obtain a better fit; 2) generalized linear mixed models, that introduce a correlation between clustered observations though the addition of random effects in the model. These two methodologies are applied to a data set obtained from an experiment to evaluate certain conditions on the germination of seeds of castor bean cultivar AL Guarany 2002 with the objective of determining the best estimation model for such data