949 resultados para monotone missing data
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Recurrent wheezing or asthma is a common problem in children that has increased considerably in prevalence in the past few decades. The causes and underlying mechanisms are poorly understood and it is thought that a numb er of distinct diseases causing similar symptoms are involved. Due to the lack of a biologically founded classification system, children are classified according to their observed disease related features (symptoms, signs, measurements) into phenotypes. The objectives of this PhD project were a) to develop tools for analysing phenotypic variation of a disease, and b) to examine phenotypic variability of wheezing among children by applying these tools to existing epidemiological data. A combination of graphical methods (multivariate co rrespondence analysis) and statistical models (latent variables models) was used. In a first phase, a model for discrete variability (latent class model) was applied to data on symptoms and measurements from an epidemiological study to identify distinct phenotypes of wheezing. In a second phase, the modelling framework was expanded to include continuous variability (e.g. along a severity gradient) and combinations of discrete and continuo us variability (factor models and factor mixture models). The third phase focused on validating the methods using simulation studies. The main body of this thesis consists of 5 articles (3 published, 1 submitted and 1 to be submitted) including applications, methodological contributions and a review. The main findings and contributions were: 1) The application of a latent class model to epidemiological data (symptoms and physiological measurements) yielded plausible pheno types of wheezing with distinguishing characteristics that have previously been used as phenotype defining characteristics. 2) A method was proposed for including responses to conditional questions (e.g. questions on severity or triggers of wheezing are asked only to children with wheeze) in multivariate modelling.ii 3) A panel of clinicians was set up to agree on a plausible model for wheezing diseases. The model can be used to generate datasets for testing the modelling approach. 4) A critical review of methods for defining and validating phenotypes of wheeze in children was conducted. 5) The simulation studies showed that a parsimonious parameterisation of the models is required to identify the true underlying structure of the data. The developed approach can deal with some challenges of real-life cohort data such as variables of mixed mode (continuous and categorical), missing data and conditional questions. If carefully applied, the approach can be used to identify whether the underlying phenotypic variation is discrete (classes), continuous (factors) or a combination of these. These methods could help improve precision of research into causes and mechanisms and contribute to the development of a new classification of wheezing disorders in children and other diseases which are difficult to classify.
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There has been a great deal of interest and debate recently concerning the linkages between inequality and health cross-nationally. Exposures to social and health inequalities likely vary as a consequence of different cultural contexts. It is important to guide research by a theoretical perspective that includes cultural and social contexts cross-nationally. If inequality affects health only under specific cultural conditions, this could explain why some of the literature that compares different societies finds no evidence of a relationship between inequality and health in certain countries. A theoretical framework is presented that combines sociological theory with constructs from cultural psychology in order to identify pathways that might lead from cultural dimensions to health inequalities. Three analyses are carried out. The first analysis explores whether there is a relationship between cultural dimensions at the societal level and self-rated health at the individual level. The findings suggest that different cultural norms at the societal level can produce both social and health inequalities, but the effects on health may differ depending on the socio-cultural context. The second analysis tests the hypothesis that health is affected by the density of social networks in a society, levels of societal trust, and inequality. The results suggest that commonly used measures of social cohesion and inequality may have both contextual and compositional effects on health in a large number of countries, and that societal measures of social cohesion and inequality interact with individual measures of social participation, trust, and income, moderating their effects on health. The third analysis explores whether value systems associated with vertical individualist societies may lead to health disparities because of their stigmatizing effects. I test the hypothesis that, within vertical individualist societies, subjective well-being will be affected by a social context where competition and the Protestant work ethic are valued, mediated by inequality. The hypothesis was not supported by the available cross-national data, most likely because of inadequate measures, missing data, and the small sample of vertical individualist countries. The overall findings demonstrate that cultural differences are important contextual factors that should not be overlooked when examining the causes of health inequalities. ^
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Coronary artery disease (CAD) is the most common cause of morbidity and mortality in the United States. While Coronary Angiography (CA) is the gold standard test to investigate coronary artery disease, Prospective gated-64 Slice Computed Tomography (Prosp-64CT) is a new non-invasive technology that uses the 64Slice computed tomography (64CT) with electrocardiographic gating to investigate coronary artery disease. The aim of the current study was to investigate the role of Body Mass Index (BMI) as a factor affecting occurrence of CA after a Prosp-64CT, as well as the quality of the Prosp-64CT. Demographic and clinical characteristics of the study population were described. A secondary analysis of data on patients who underwent a Prosp-64CT for evaluation of coronary artery disease was performed. Seventy seven patients who underwent Prosp-64CT for evaluation for coronary artery disease were included. Fifteen patients were excluded because they had missing data regarding BMI, quality of the Prosp-64CT or CA. Thus, a total of 62 patients were included in the final analysis. The mean age was 56.2 years. The mean BMI was 31.3 kg/m 2. Eight (13%) patients underwent a CA within one month of Prosp-64CT. Eight (13%) patients had a poor quality Prosp-64CT. There was significant association of higher BMI as a factor for occurrence of CA post Prosp-64CT (P<0.05). There was a trend, but no statistical significance was observed for the association of being obese and occurrence of CA (P=0.06). BMI, as well as obesity, were not found to be significantly associated with poor quality of Prosp-64CT (P=0.19 and P=0.76, respectively). In conclusion, BMI was significantly associated with occurrence of CA within one month of Prosp-64CT. Thus, in patients with a higher BMI, diagnostic investigation with both tests could be avoided; rather, only a CA could be performed. However, the relationship of BMI to quality of Prosp-64CT needs to be further investigated since the sample size of the current study was small.^
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There are two practical challenges in the phase I clinical trial conduct: lack of transparency to physicians, and the late onset toxicity. In my dissertation, Bayesian approaches are used to address these two problems in clinical trial designs. The proposed simple optimal designs cast the dose finding problem as a decision making process for dose escalation and deescalation. The proposed designs minimize the incorrect decision error rate to find the maximum tolerated dose (MTD). For the late onset toxicity problem, a Bayesian adaptive dose-finding design for drug combination is proposed. The dose-toxicity relationship is modeled using the Finney model. The unobserved delayed toxicity outcomes are treated as missing data and Bayesian data augment is employed to handle the resulting missing data. Extensive simulation studies have been conducted to examine the operating characteristics of the proposed designs and demonstrated the designs' good performances in various practical scenarios.^
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Data from the 2009–2011 School Physical Activity and Nutrition (SPAN) project were analyzed to examine the association between bullied status at school during the past six months and engaging in five or more days of physical activity during the past seven days in a population of 8th and 11th grade Texas youths after stratifying by gender. As a secondary aim, this study also examined the association between weight status and the prevalence of bullied status at school. The final sample size for this study, after excluding missing data, consisted of 6,246 8th and 11th grade youths (girls, n= 3,237; boys, n=3,009) representing a total of 518,838 youths from 8th and 11th grade. Results from the multiple logistic regression adjusting for weight status, grade, and ethnicity, indicate that girls with a bullied status of at least two or three times per month had significantly lower odds of engaging in five or more days of physical activity during the past seven days than girls who were never bullied at school (ORadj=0.62; 95% CI, 0.40, 0.96). Conversely, girls who reported a bullied status of at least once per week were significantly more likely to engage in five or more days of physical activity during the past seven days compared to girls who were never bullied at school (ORadj=3.44; 95% CI, 1.56, 7.63). No significant associations between bullied status and engaging in five or more days of physical activity during the past seven days were found for boys. Bullied status differed significantly across weight status for 8th grade girls (χ2(6)=63.7, p<.05) and 11th grade boys (χ2(6) =94.93, p<.05), with overweight and obese youths reporting a higher prevalence of being bullied once or twice, at least two or three times per month, and at least once per week than their normal weight peers. Our finding that girls with bullied status of at least once per week were more likely to engage in five or more days of physical activity than girls who were never bullied warrants future qualitative research to identify potential explanations for such results. Future research on relational and weight-based bullying is also needed and may help explain the inconsistent findings between bullied status and engaging in physical activity in girls.^
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Background: Once thought to be eradicated, pertussis is now making a steady comeback throughout Texas and the United States. Pertussis can have an effect on all demographics, but infants have the greatest health concern as they suffer the highest case-fatality rate. The objective of this study was to create and report a comprehensive summary of confirmed or probable pertussis cases in a Texas County during the 2008 through 2012 time period.^ Methods: A cross-sectional study design was used to show at risk populations in a Texas county using descriptive statistics of data from probable and confirmed pertussis cases in this Texas County from 2008-2012. Data was collected during routine pertussis investigations conducted by the local health department of this Texas County.^ Results: There was a sharp increase in pertussis cases seen in this county in 2012. Hispanics made up the majority of cases (74.9%) as compared to 12.8% of cases among Whites, 3.1% of cases among Blacks and 9.2% of cases among unknown/other. The population of Hispanics within this county was 58.9%. Almost a quarter of cases (24.2%) in this study were hospitalized. There was no difference identified in the proportion of male sources of exposure (48.9%) as compared to female (51.1%). Household contacts were the main sources of exposure: siblings (29.2%), fathers (14.5%), children (14.6%), and mothers (12.5%).^ Conclusion: Prevention intervention needs to be designed to target vulnerable populations and reduce the effect of this sometimes fatal disease. These results show pertussis proportionally has a greater effect on Hispanics. Additional research needs to be conducted on risk factors such as household crowding and immunization status among Hispanics to identify if ethnicity plays a role in risk of transmission of pertussis. The results were limited due to the large amount of missing data in vaccination history and identification of source of exposure.^
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As a part of the shipboard scientific program, interstitial waters were routinely analyzed for pH, alkalinity, salinity, chlorinity, calcium, and magnesium during Leg 116. Unfortunately, the tables containing these data for Sites 718 and 719 were inadvertently omitted from the Initial Results volume (Cochran, Stow et al., 1989, doi:10.2973/odp.proc.ir.116.1989). The missing data are presented here (Tables 1-3) along with the Site 717 data, reproduced for completeness.
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Esta Tesis se centra en el desarrollo de un método para la reconstrucción de bases de datos experimentales incompletas de más de dos dimensiones. Como idea general, consiste en la aplicación iterativa de la descomposición en valores singulares de alto orden sobre la base de datos incompleta. Este nuevo método se inspira en el que ha servido de base para la reconstrucción de huecos en bases de datos bidimensionales inventado por Everson y Sirovich (1995) que a su vez, ha sido mejorado por Beckers y Rixen (2003) y simultáneamente por Venturi y Karniadakis (2004). Además, se ha previsto la adaptación de este nuevo método para tratar el posible ruido característico de bases de datos experimentales y a su vez, bases de datos estructuradas cuya información no forma un hiperrectángulo perfecto. Se usará una base de datos tridimensional de muestra como modelo, obtenida a través de una función transcendental, para calibrar e ilustrar el método. A continuación se detalla un exhaustivo estudio del funcionamiento del método y sus variantes para distintas bases de datos aerodinámicas. En concreto, se usarán tres bases de datos tridimensionales que contienen la distribución de presiones sobre un ala. Una se ha generado a través de un método semi-analítico con la intención de estudiar distintos tipos de discretizaciones espaciales. El resto resultan de dos modelos numéricos calculados en C F D . Por último, el método se aplica a una base de datos experimental de más de tres dimensiones que contiene la medida de fuerzas de una configuración ala de Prandtl obtenida de una campaña de ensayos en túnel de viento, donde se estudiaba un amplio espacio de parámetros geométricos de la configuración que como resultado ha generado una base de datos donde la información está dispersa. ABSTRACT A method based on an iterative application of high order singular value decomposition is derived for the reconstruction of missing data in multidimensional databases. The method is inspired by a seminal gappy reconstruction method for two-dimensional databases invented by Everson and Sirovich (1995) and improved by Beckers and Rixen (2003) and Venturi and Karniadakis (2004). In addition, the method is adapted to treat both noisy and structured-but-nonrectangular databases. The method is calibrated and illustrated using a three-dimensional toy model database that is obtained by discretizing a transcendental function. The performance of the method is tested on three aerodynamic databases for the flow past a wing, one obtained by a semi-analytical method, and two resulting from computational fluid dynamics. The method is finally applied to an experimental database consisting in a non-exhaustive parameter space measurement of forces for a box-wing configuration.
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As análises biplot que utilizam os modelos de efeitos principais aditivos com inter- ação multiplicativa (AMMI) requerem matrizes de dados completas, mas, frequentemente os ensaios multiambientais apresentam dados faltantes. Nesta tese são propostas novas metodologias de imputação simples e múltipla que podem ser usadas para analisar da- dos desbalanceados em experimentos com interação genótipo por ambiente (G×E). A primeira, é uma nova extensão do método de validação cruzada por autovetor (Bro et al, 2008). A segunda, corresponde a um novo algoritmo não-paramétrico obtido por meio de modificações no método de imputação simples desenvolvido por Yan (2013). Também é incluído um estudo que considera sistemas de imputação recentemente relatados na literatura e os compara com o procedimento clássico recomendado para imputação em ensaios (G×E), ou seja, a combinação do algoritmo de Esperança-Maximização com os modelos AMMI ou EM-AMMI. Por último, são fornecidas generalizações da imputação simples descrita por Arciniegas-Alarcón et al. (2010) que mistura regressão com aproximação de posto inferior de uma matriz. Todas as metodologias têm como base a decomposição por valores singulares (DVS), portanto, são livres de pressuposições distribucionais ou estruturais. Para determinar o desempenho dos novos esquemas de imputação foram realizadas simulações baseadas em conjuntos de dados reais de diferentes espécies, com valores re- tirados aleatoriamente em diferentes porcentagens e a qualidade das imputações avaliada com distintas estatísticas. Concluiu-se que a DVS constitui uma ferramenta útil e flexível na construção de técnicas eficientes que contornem o problema de perda de informação em matrizes experimentais.
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El objetivo es describir las limitaciones y las recomendaciones metodológicas identificadas por los autores de artículos originales sobre inmigración y salud en España. Se realizó una revisión bibliográfica de artículos originales publicados en español e inglés entre 1998 y 2012, combinando descriptores de inmigración y salud. Se incluyeron 311 artículos; de ellos, 176 (56,6%) mencionaban limitaciones y 15 (4,8%) emitían recomendaciones. Entre las limitaciones más mencionadas destacan el reducido tamaño de las muestras, problemas de validez interna y representatividad de la muestra con infrarrepresentación o sobrerrepresentación de determinados grupos, problemas de validez de la información recogida y datos faltantes relacionados sobre todo con los instrumentos de medición, y ausencia de variables clave de ajuste o estratificación. En función de los resultados obtenidos, se proponen una serie de recomendaciones para minimizar las limitaciones habituales y avanzar en la calidad de los trabajos científicos sobre inmigración y salud en nuestro ámbito.
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Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014
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IMPORTANCE Obesity is a risk factor for deep vein thrombosis of the leg and pulmonary embolism. To date, however, whether obesity is associated with adult cerebral venous thrombosis (CVT) has not been assessed. OBJECTIVE To assess whether obesity is a risk factor for CVT. DESIGN, SETTING, AND PARTICIPANTS A case-control study was performed in consecutive adult patients with CVT admitted from July 1, 2006 (Amsterdam), and October 1, 2009 (Berne), through December 31, 2014, to the Academic Medical Center in Amsterdam, the Netherlands, or Inselspital University Hospital in Berne, Switzerland. The control group was composed of individuals from the control population of the Multiple Environmental and Genetic Assessment of Risk Factors for Venous Thrombosis study, which was a large Dutch case-control study performed from March 1, 1999, to September 31, 2004, and in which risk factors for deep vein thrombosis and pulmonary embolism were assessed. Data analysis was performed from January 2 to July 12, 2015. MAIN OUTCOMES AND MEASURES Obesity was determined by body mass index (BMI). A BMI of 30 or greater was considered to indicate obesity, and a BMI of 25 to 29.99 was considered to indicate overweight. A multiple imputation procedure was used for missing data. We adjusted for sex, age, history of cancer, ethnicity, smoking status, and oral contraceptive use. Individuals with normal weight (BMI <25) were the reference category. RESULTS The study included 186 cases and 6134 controls. Cases were younger (median age, 40 vs 48 years), more often female (133 [71.5%] vs 3220 [52.5%]), more often used oral contraceptives (97 [72.9%] vs 758 [23.5%] of women), and more frequently had a history of cancer (17 [9.1%] vs 235 [3.8%]) compared with controls. Obesity (BMI ≥30) was associated with an increased risk of CVT (adjusted odds ratio [OR], 2.63; 95% CI, 1.53-4.54). Stratification by sex revealed a strong association between CVT and obesity in women (adjusted OR, 3.50; 95% CI, 2.00-6.14) but not in men (adjusted OR, 1.16; 95% CI, 0.25-5.30). Further stratification revealed that, in women who used oral contraceptives, overweight and obesity were associated with an increased risk of CVT in a dose-dependent manner (BMI 25.0-29.9: adjusted OR, 11.87; 95% CI, 5.94-23.74; BMI ≥30: adjusted OR, 29.26; 95% CI, 13.47-63.60). No association was found in women who did not use oral contraceptives. CONCLUSIONS AND RELEVANCE Obesity is a strong risk factor for CVT in women who use oral contraceptives.
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Thesis (Master's)--University of Washington, 2016-06
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The Center for Epidemiologic Studies Depression Scale (CES-D) is frequently used in epidemiological surveys to screen for depression, especially among older adults. This article addresses the problem of non-completion of a short form of the CES-D (CESD-10) in a mailed survey of 73- to 78-year-old women enrolled in the Australian Longitudinal Study on Women's Health. Completers of the CESD-10 had more education, found it easier to manage on available income and reported better physical and mental health. The Medical Outcomes Study Short Form Health Survey (SF-36) scores for non-completers were intermediate between those for women classified as depressed and not depressed using the CESD-10. Indicators of depression had an inverted U-shaped relationship with the number of missing CESD- 10 items and were most frequent for women with two to seven items missing. Future research should pay particular attention to the level of missing data in depression scales and report its potential impact on estimates of depression.
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We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.