Statistical issues on studies of mixed longitudinal design

Mixed longitudinal designs are important study designs for many areas of medical research. Mixed longitudinal studies have several advantages over cross-sectional or pure longitudinal studies, including shorter study completion time and ability to separate time and age effects, thus are an attractive choice. Statistical methodology used in general longitudinal studies has been rapidly developing within the last few decades. Common approaches for statistical modeling in studies with mixed longitudinal designs have been the linear mixed-effects model incorporating an age or time effect. The general linear mixed-effects model is considered an appropriate choice to analyze repeated measurements data in longitudinal studies. However, common use of linear mixed-effects model on mixed longitudinal studies often incorporates age as the only random-effect but fails to take into consideration the cohort effect in conducting statistical inferences on age-related trajectories of outcome measurements. We believe special attention should be paid to cohort effects when analyzing data in mixed longitudinal designs with multiple overlapping cohorts. Thus, this has become an important statistical issue to address. ^ This research aims to address statistical issues related to mixed longitudinal studies. The proposed study examined the existing statistical analysis methods for the mixed longitudinal designs and developed an alternative analytic method to incorporate effects from multiple overlapping cohorts as well as from different aged subjects. The proposed study used simulation to evaluate the performance of the proposed analytic method by comparing it with the commonly-used model. Finally, the study applied the proposed analytic method to the data collected by an existing study Project HeartBeat!, which had been evaluated using traditional analytic techniques. Project HeartBeat! is a longitudinal study of cardiovascular disease (CVD) risk factors in childhood and adolescence using a mixed longitudinal design. The proposed model was used to evaluate four blood lipids adjusting for age, gender, race/ethnicity, and endocrine hormones. The result of this dissertation suggest the proposed analytic model could be a more flexible and reliable choice than the traditional model in terms of fitting data to provide more accurate estimates in mixed longitudinal studies. Conceptually, the proposed model described in this study has useful features, including consideration of effects from multiple overlapping cohorts, and is an attractive approach for analyzing data in mixed longitudinal design studies.^

Instrumental variable method for the causal relationship between soluble receptor for advanced glycation end-products (sRAGE) and risk of pancreatic cancer

This thesis project is motivated by the potential problem of using observational data to draw inferences about a causal relationship in observational epidemiology research when controlled randomization is not applicable. Instrumental variable (IV) method is one of the statistical tools to overcome this problem. Mendelian randomization study uses genetic variants as IVs in genetic association study. In this thesis, the IV method, as well as standard logistic and linear regression models, is used to investigate the causal association between risk of pancreatic cancer and the circulating levels of soluble receptor for advanced glycation end-products (sRAGE). Higher levels of serum sRAGE were found to be associated with a lower risk of pancreatic cancer in a previous observational study (255 cases and 485 controls). However, such a novel association may be biased by unknown confounding factors. In a case-control study, we aimed to use the IV approach to confirm or refute this observation in a subset of study subjects for whom the genotyping data were available (178 cases and 177 controls). Two-stage IV method using generalized method of moments-structural mean models (GMM-SMM) was conducted and the relative risk (RR) was calculated. In the first stage analysis, we found that the single nucleotide polymorphism (SNP) rs2070600 of the receptor for advanced glycation end-products (AGER) gene meets all three general assumptions for a genetic IV in examining the causal association between sRAGE and risk of pancreatic cancer. The variant allele of SNP rs2070600 of the AGER gene was associated with lower levels of sRAGE, and it was neither associated with risk of pancreatic cancer, nor with the confounding factors. It was a potential strong IV (F statistic = 29.2). However, in the second stage analysis, the GMM-SMM model failed to converge due to non- concaveness probably because of the small sample size. Therefore, the IV analysis could not support the causality of the association between serum sRAGE levels and risk of pancreatic cancer. Nevertheless, these analyses suggest that rs2070600 was a potentially good genetic IV for testing the causality between the risk of pancreatic cancer and sRAGE levels. A larger sample size is required to conduct a credible IV analysis.^

Part of the global DOC versus AOU (dissolved organic carbon/apparent oxygen utilization) data compilation, Pacific Ocean

Total organic carbon (TOC) was analyzed on four transects along 140°W in 1992 using a high temperature combustion/discrete injection (HTC/DI) analyzer. For two of the transects, the analyses were conducted on-board ship. Mixed-layer concentrations of organic carbon varied from about 80 µM C at either end of the transect (12°N and 12°S) to about 60 µM C at the equator. Total organic carbon concentrations decreased rapidly below the mixed-layer to about 38-40 µM C at 1000 m across the transect. Little variation was observed below this depth; deep water concentrations below 2000 m were virtually monotonic at about 36 µM C. Repeat measurements made on subsequent cruises consistently found the same concentrations at 1000 m or deeper, but substantial variations were observed in the mixed-layer and the upper water column above 400 m depth. Linear mixing models of total organic carbon versus sigmaT exhibited zones of organic carbon formation and consumption. TOC was found to be inversely correlated with apparent oxygen utilization (AOU) in the region between the mixed-layer and the oxygen minimum. In the mixed-layer, TOC concentrations varied seasonally. Part of the variations in TOC at the equator was driven by changes in the upwelling rate in response to variations in physical forcing related to an El Niño and to the passage of tropical instability waves. TOC export fluxes, calculated from simple box models, averaged 8±4 mmol C/m**2/day at the equator and also varied seasonally. These export fluxes account for 50-75% of the total carbon deficit and are consistent with other estimates and model predictions.

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

Whale sightings, group sizes and krill biomass in West Greenland in 2005

This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.

(Table 2) Carbon and nitrogen isotopic ratios in blood sampled from arctic foxes (Vulpes lagopus) on Bylot Island between 2003-2008

Inter-individual variation in diet within generalist animal populations is thought to be a widespread phenomenon but its potential causes are poorly known. Inter-individual variation can be amplified by the availability and use of allochthonous resources, i.e., resources coming from spatially distinct ecosystems. Using a wild population of arctic fox as a study model, we tested hypotheses that could explain variation in both population and individual isotopic niches, used here as proxy for the trophic niche. The arctic fox is an opportunistic forager, dwelling in terrestrial and marine environments characterized by strong spatial (arctic-nesting birds) and temporal (cyclic lemmings) fluctuations in resource abundance. First, we tested the hypothesis that generalist foraging habits, in association with temporal variation in prey accessibility, should induce temporal changes in isotopic niche width and diet. Second, we investigated whether within-population variation in the isotopic niche could be explained by individual characteristics (sex and breeding status) and environmental factors (spatiotemporal variation in prey availability). We addressed these questions using isotopic analysis and Bayesian mixing models in conjunction with linear mixed-effects models. We found that: i) arctic fox populations can simultaneously undergo short-term (i.e., within a few months) reduction in both isotopic niche width and inter-individual variability in isotopic ratios, ii) individual isotopic ratios were higher and more representative of a marine-based diet for non-breeding than breeding foxes early in spring, and iii) lemming population cycles did not appear to directly influence the diet of individual foxes after taking their breeding status into account. However, lemming abundance was correlated to proportion of breeding foxes, and could thus indirectly affect the diet at the population scale.

Risk assessment of the spanish national railway system

The principal risks in the railway industry are mainly associated with collisions, derailments and level crossing accidents. An understanding of the nature of previous accidents on the railway network is required to identify potential causes and develop safety systems and deploy safety procedures. Risk assessment is a process for determining the risk magnitude to assist with decision-making. We propose a three-step methodology to predict the mean number of fatalities in railway accidents. The first is to predict the mean number of accidents by analyzing generalized linear models and selecting the one that best fits to the available historical data on the basis of goodness-offit statistics. The second is to compute the mean number of fatalities per accident and the third is to estimate the mean number of fatalities. The methodology is illustrated on the Spanish railway system. Statistical models accounting for annual and grouped data for the 1992-2009 time period have been analyzed. After identifying the models for broad and narrow gauges, we predicted mean number of accidents and the number of fatalities for the 2010-18 time period.

Programa Bolsa Família na coorte de nascimentos de Pelotas, 2004: focalização e impactos no IMC/Idade, obesidade e composição corporal de crianças

Introdução: O Programa Bolsa Família é a principal estratégia brasileira para amenizar a pobreza e vulnerabilidade social, com diferentes impactos na vida dos beneficiários. O aumento da renda, em função do benefício, poderia trazer resultados positivos na alimentação, uma vez que possibilitam uma maior diversidade da dieta. Porém, poderia trazer resultados negativos como a ingestão excessiva de energia e consequente aumento da adiposidade. As avaliações dos impactos do programa em termos de obesidade e massa gorda de crianças são inexistentes. Objetivo: Avaliar o impacto do Programa Bolsa Família no estado nutricional (IMC/idade) e na composição corporal aos 6 anos de idade entre as crianças da Coorte de Nascimentos de Pelotas (RS), 2004. Métodos: Os dados foram provenientes da integração dos bancos da Coorte de Nascimentos de Pelotas de 2004 e do Cadastro Único do Governo Federal. Foi realizada análise descritiva da cobertura e focalização do programa, com informações do nascimento e dos 6 anos de idade (n=4231). Considerou-se focalização o percentual de elegíveis entre o total de beneficiários e cobertura o percentual de famílias elegíveis que são beneficiárias do programa. Nos modelos de impacto (n=3446), as exposições principais foram o recebimento do benefício: beneficiário em 2010, no período de 2004-2010; o valor médio mensal recebido e o tempo de recebimento. Foram gerados modelos de regressão linear para os desfechos score-Z do índice de massa corporal por idade (IMC/I), percentual e índice de massa gorda (IMG), e percentual e índice de massa livre de gordura (IMLG); e de Poisson, com ajuste robusto, para o desfecho obesidade (score-Z IMC/I 2), todos estratificados por sexo. As informações antropométricas e de composição corporal (BOD POD) foram obtidas do acompanhamento aos 6-7 anos de idade. Potenciais fatores de confusão foram identificados por modelo hierárquico e por um diagrama causal (DAG). Para analisar os impactos foram usadas como medidas de efeito a diferença de médias na regressão linear múltipla (IMC/I, por cento MG, IMG, por cento MLG e IMLG, variáveis contínuas) e a razão de prevalência (obesidade, variável binária). Para permanecer no modelo, considerou-se valor p0,20. A análise dos dados foi realizada por meio do software STATA. Resultados: Entre 2004-2010, a proporção de famílias beneficiárias na coorte aumentou (11 por cento para 34 por cento ) enquanto, de acordo com a renda familiar, a proporção de famílias elegíveis diminui (29 por cento para 16 por cento ). No mesmo período, a cobertura do programa aumentou tanto pela renda familiar quanto pelo IEN. Já a focalização caiu de 78 por cento para 32 por cento de acordo com a renda familiar e, de acordo com o IEN, manteve-se em 37 por cento . A média (não ajustada) de IMC e de MG dos não beneficiários foi superior a dos não beneficiários tanto em meninos quanto em meninas. Meninos do 3º tercil de valor per capita recebido e meninas com menos de 7 meses de benefício em 2010 tiveram IMC maior do que, respectivamente, aqueles dos demais tercis e daquelas com mais de 7 meses de benefício em 2010; esse padrão foi semelhante para obesidade. Meninas não beneficiárias tiveram MG maior do que as beneficiárias e superior também aos meninos, independente de ser beneficiário ou não. Em relação à MLG observou-se um comportamento contrário, no qual meninas beneficiárias tiveram maior MLG, quando comparadas com meninas não beneficiárias e, meninos quando comparados com meninas. Nos modelos de regressão ajustados, não houve diferença significativa entre beneficiários e não beneficiários em nenhum desfecho. Conclusões: De acordo com os resultados, as famílias que receberam maiores valores per capita parecem incluir crianças com maior média de IMC. O programa, nessa análise, parece não ter impacto sobre a composição corporal das crianças, nem em termos de massa gorda, tampouco em termos de massa livre de gordura.

Prospective longitudinal study of subcortical brain volumes in individuals at high familial risk of mood disorders with or without subsequent onset of depression

Subcortical volumetric brain abnormalities have been observed in mood disorders. However, it is unknown whether these reflect adverse effects predisposing to mood disorders or emerge at illness onset. Magnetic resonance imaging was conducted at baseline and after two years in 111 initially unaffected young adults at increased risk of mood disorders because of a close family history of bipolar disorder and 93 healthy controls (HC). During the follow-up, 20 high-risk subjects developed major depressive disorder (HR-MDD), with the others remaining well (HR-well). Volumes of the lateral ventricles, caudate, putamen, pallidum, thalamus, hippocampus and amygdala were extracted for each hemisphere. Using linear mixed-effects models, differences and longitudinal changes in subcortical volumes were investigated between groups (HC, HR-MDD, HR-well). There were no significant differences for any subcortical volume between groups controlling for multiple testing. Additionally, no significant differences emerged between groups over time. Our results indicate that volumetric subcortical brain abnormalities of these regions using the current method appear not to form familial trait markers for vulnerability to mood disorders in close relatives of bipolar disorder patients over the two-year time period studied. Moreover, they do not appear to reduce in response to illness onset at least for the time period studied.

Heat stress, heat strain, and productivity in Washington State tree fruit harvesters

Thesis (Master's)--University of Washington, 2016-06

The 2014 chikungunya virus outbreak in the U.S. Virgin Islands: epidemiology, long-term health outcomes, and economic burden

Thesis (Ph.D.)--University of Washington, 2016-06

Environmental Enteropathy and Fibroblast Growth Factor 21 are associated with early childhood growth in Bangladesh

Thesis (Ph.D.)--University of Washington, 2016-06

Adherence to a Bronchiolitis Clinical Pathway is Associated with Decreased Length of Stay and Costs

Thesis (Master's)--University of Washington, 2016-06

EM optimization of latent-variable density models

There is currently considerable interest in developing general non-linear density models based on latent, or hidden, variables. Such models have the ability to discover the presence of a relatively small number of underlying `causes' which, acting in combination, give rise to the apparent complexity of the observed data set. Unfortunately, to train such models generally requires large computational effort. In this paper we introduce a novel latent variable algorithm which retains the general non-linear capabilities of previous models but which uses a training procedure based on the EM algorithm. We demonstrate the performance of the model on a toy problem and on data from flow diagnostics for a multi-phase oil pipeline.

Applications of Reissner's principle to structural dynamics

The analysis and prediction of the dynamic behaviour of s7ructural components plays an important role in modern engineering design. :n this work, the so-called "mixed" finite element models based on Reissnen's variational principle are applied to the solution of free and forced vibration problems, for beam and :late structures. The mixed beam models are obtained by using elements of various shape functions ranging from simple linear to complex cubic and quadratic functions. The elements were in general capable of predicting the natural frequencies and dynamic responses with good accuracy. An isoparametric quadrilateral element with 8-nodes was developed for application to thin plate problems. The element has 32 degrees of freedom (one deflection, two bending and one twisting moment per node) which is suitable for discretization of plates with arbitrary geometry. A linear isoparametric element and two non-conforming displacement elements (4-node and 8-node quadrilateral) were extended to the solution of dynamic problems. An auto-mesh generation program was used to facilitate the preparation of input data required by the 8-node quadrilateral elements of mixed and displacement type. Numerical examples were solved using both the mixed beam and plate elements for predicting a structure's natural frequencies and dynamic response to a variety of forcing functions. The solutions were compared with the available analytical and displacement model solutions. The mixed elements developed have been found to have significant advantages over the conventional displacement elements in the solution of plate type problems. A dramatic saving in computational time is possible without any loss in solution accuracy. With beam type problems, there appears to be no significant advantages in using mixed models.