Global ETD Search

31	Statistical inference for joint modelling of longitudinal and survival data Li, Qiuju January 2014 (has links) In longitudinal studies, data collected within a subject or cluster are somewhat correlated by their very nature and special cares are needed to account for such correlation in the analysis of data. Under the framework of longitudinal studies, three topics are being discussed in this thesis. In chapter 2, the joint modelling of multivariate longitudinal process consisting of different types of outcomes are discussed. In the large cohort study of UK north Stafforshire osteoarthritis project, longitudinal trivariate outcomes of continuous, binary and ordinary data are observed at baseline, year 3 and year 6. Instead of analysing each process separately, joint modelling is proposed for the trivariate outcomes to account for the inherent association by introducing random effects and the covariance matrix G. The influence of covariance matrix G on statistical inference of fixed-effects parameters has been investigated within the Bayesian framework. The study shows that by joint modelling the multivariate longitudinal process, it can reduce the bias and provide with more reliable results than it does by modelling each process separately. Together with the longitudinal measurements taken intermittently, a counting process of events in time is often being observed as well during a longitudinal study. It is of interest to investigate the relationship between time to event and longitudinal process, on the other hand, measurements taken for the longitudinal process may be potentially truncated by the terminated events, such as death. Thus, it may be crucial to jointly model the survival and longitudinal data. It is popular to propose linear mixed-effects models for the longitudinal process of continuous outcomes and Cox regression model for survival data to characterize the relationship between time to event and longitudinal process, and some standard assumptions have been made. In chapter 3, we try to investigate the influence on statistical inference for survival data when the assumption of mutual independence on random error of linear mixed-effects models of longitudinal process has been violated. And the study is conducted by utilising conditional score estimation approach, which provides with robust estimators and shares computational advantage. Generalised sufficient statistic of random effects is proposed to account for the correlation remaining among the random error, which is characterized by the data-driven method of modified Cholesky decomposition. The simulation study shows that, by doing so, it can provide with nearly unbiased estimation and efficient statistical inference as well. In chapter 4, it is trying to account for both the current and past information of longitudinal process into the survival models of joint modelling. In the last 15 to 20 years, it has been popular or even standard to assume that longitudinal process affects the counting process of events in time only through the current value, which, however, is not necessary to be true all the time, as recognised by the investigators in more recent studies. An integral over the trajectory of longitudinal process, along with a weighted curve, is proposed to account for both the current and past information to improve inference and reduce the under estimation of effects of longitudinal process on the risk hazards. A plausible approach of statistical inference for the proposed models has been proposed in the chapter, along with real data analysis and simulation study. 519.5
32	OPTICAL COHERENCE TOMOGRAPHY TO MEASURE EFFECTS OF AUTOLOGOUS MESENCHYMAL STEM CELL TRANSPLANT IN MULTIPLE SCLEROSIS PATIENTS Rossman, Ian 05 June 2017 (has links) No description available. Medicine Multiple Sclerosis mesenchymal stem cell optical coherence tomography stem cell transplant phase 1 clinical trial linear mixed effects model retinal ganglion cell layer retinal nerve fiber layer neuroprotection
33	Temperature-Induced Shifts in Size Spectra of Fish Communities in lakes / Temperaturinducerande förändringar i storleksspektra av fisksamhällen i sjöar Åberg, Olivia January 2024 (has links) Climate change affects lakes, seas and running water globally, but the long-term effects on aquatic ecosystems, including fish communities, are complex and difficult to predict. Previous research has shown that changes in temperature, for example, can lead to shifts in fish species distribution and reductions in body size within fish communities. This study aims to investigate the impact of temperature on size distribution of individuals in fish communities by examining variations in so-called size spectrum and mean body size in ten Swedish lakes over the period 1994-2023. Data were collected from Swedish monitoring programs and analyzed using linear mixed-effects models. The result indicates a significant negative effect of temperature on the size spectrum and mean body size, meaning the number of small individuals increases while the number of large ones decreases. The size spectrum also shows a declining trend over time in several of the lakes, highlighting a shift in the size distribution of fish. These findings support the use of the size spectrum as an indicator of the impacts of climate change on freshwater ecosystems. The results of this study found a clearer link between temperature changes and size distribution compared to biomass, which supports the usefulness of size distribution as an indicator. Understanding these relationships is crucial for informing management and conservation strategies aimed at preserving lake ecosystems and the functions and ecosystem services that fish provide, including food and recreational opportunities. The study further contributes to the existing evidence that climate change is reshaping fish communities and aquatic ecosystems, underscoring the need for adaptive management to mitigate these effects and ensure sustainability of fish stocks for future generations. / Klimatförändringarna påverkar sjöar, hav och rinnande vatten globalt, men långsiktiga effekter på akvatiska ekosystem, inklusive fisksamhällens, är komplexa och svåra att förutse. Tidigare studier har visat att förändringar i temperatur till exempel kan leda till skiften i fiskarters utbredning och minskningar i kroppsstorlek i fisksamhällen. Denna studie syftar till att undersöka temperaturens inverkan på storleksfördelningen av individer i fisksamhällen genom att undersöka variation i det så kallade storleksspektrumets lutning och medelstorlek i tio svenska sjöar under perioden 1994–2023. Data samlades in från svenska övervakningsprogram för sjöar och analyserades med hjälp av linjära mixade effektmodeller. Resultaten indikerar en signifikant negativ effekt av temperatur på storleksspektrumets lutning och medelkroppsstorlek, dvs. antalet små individer ökar relativt antalet stora. Storlekspektrumets lutning visar också en nedåtgående trend över tid i flera av sjöarna, vilket belyser att fiskarnas storleksfördelning har skiftat mot relativt fler små individer i vissa sjöar. Dessa fynd styrker användningen av storleksspektrum som en indikator på klimatförändringarnas effekter på sötvattensekosystem. Resultat från denna studie visar också en tydligare koppling av förändrad temperatur på storleksfördelning än biomassor av fisk och växtplankton, vilket styrker nyttan av storleksfördelning som indikator. Att förstå dessa samband är avgörande för att vägleda förvaltnings- och bevarande strategier som syftar till att bevara sjöekosystem, de funktioner samt ekosystemtjänster som fiskar tillhandahåller, såsom mat och rekreationsmöjligheter. Studien bidrar till redan existerande bevis på att klimatförändringarna omformar fisksamhällen och akvatiska ekosystem, vilket tydliggör behovet av adaptiv förvaltning för att mildra dessa effekter och säkerställa starka fiskbestånd för framtida generationer. Climate change Lakes Aquatic ecosystem Fish size distribution Size spectrum Linear mixed-effects model Klimatuppvärmning Sjöar Akvatiska ekosystem Fiskstorleksfördelning Storleksspektrum Linjär blandade effekter modell Engineering and Technology Teknik och teknologier Ecology Ekologi
34	資本資產定價模型之穩健估計分析顏培俊, Yen, Pei-Chun Unknown Date (has links) 長期性資料(longitudinal data)的最主要特徵是為對多個被觀測個體在不同的時間點上重複測量一個或多個反應變數。而在分析長期性資料的方法中，Laird & Ware(1982)建議以線性混合效果模型(linear mixed effects model，LME)來進行估計分析，此模型方法中，資料可以允許遺失值，並可將受測個體間與個體內的變異分開說明。另在配適最小平方法(OLS)的迴歸模型中，係數估計經常會受到異常值的影響，而Rousseeuw & Leroy(1987)提出最小消去平方法(least trimmed squares，LTS)的穩健迴歸模型，即是解決最小平方法中對於異常值敏感的問題。本研究主要針對台灣股票預期報酬之三種模型：資本資產定價模型、特徵模型、因子模型分別以OLS、LTS、LME三種估計方法做配適，並比較配適模型之適當與否，樣本資料為民國七十年七月至九十年六月共252個月516家上市公司股票報酬。實證結果顯示，不論是採用OLS、LTS、LME的估計方法，股票報酬解釋變數：系統風險、公司規模、帳面權益對市值比、SMB、HML皆為股票報酬的顯著解釋因子；而在模型比較方面，不論是配適資本資產定價模型、特徵模型或因子模型，LME都較OLS為較適當配適模型。這顯示了在分析長期性資料時，LME的確是一個較佳的統計分析模型。長期性資料線性混合效果模型穩健迴歸模型資本資產定價模型因子模型 Longitudinal Data Linear Mixed Effects Model Robust Regression Model CAPM Factor Model
35	以穩健估計及長期資料分析觀點探討資本資產定價模型 / On the CAPM from the Views of Robustness and Longitudinal Analysis 呂倩如, Lu Chien-ju Unknown Date (has links) 資本資產定價模型 (CAPM) 由Sharp (1964)、Lintner (1965)及Black (1972)發展出後，近年來已被廣泛的應用於衡量證券之預期報酬率與風險間之關係。一般而言，衡量結果之估計有兩個階段，首先由時間序列分析估計出貝它(beta)係數，然後再檢定廠商或投資組合之平均報酬率與貝它係數之關係。 Fama與MacBeth (1973)利用最小平方法估計貝它係數，再將由橫斷面迴歸方法所得出之斜率係數加以平均後，以統計t-test檢定之。然而以最小平方法估計係數，其估計值很容易受離群值之影響，因此本研究考慮以穩健估計 (robust estimator)來避免此一問題。另外，本研究亦將長期資料分析 (longitudinal data analysis) 引入CAPM裡，期望能檢定貝它係數是否能確實有效地衡量出系統性風險。論文中以台灣股票市場電子業之實證分析來比較上述不同方法對CAPM的結果，資料蒐集期間為1998年9月至2001年12月之月資料。研究結果顯示出，穩健估計相對於最小平方法就CAPM有較佳的解釋力。而長期資料分析模型更用來衡量債券之超額報酬部分，是否會依上、中、下游或公司之不同而不同。 / The Capital Asset Pricing Model (CAPM) of Sharp (1964), Lintner (1965) and Black (1972) has been widely used in measuring the relationship between the expected return on a security and its risk in the recent years. It consists of two stages to estimate the relationship between risk and expected return. The first one is that betas are estimated from time series regressions, and the second is that the relationship between mean returns and betas is tested across firms or portfolios. Fama and MacBeth (1973) first used ordinary least squares (OLS) to estimate beta and took time series averages of the slope coefficients from monthly cross-sectional regressions in such studies. However it is well known that OLS is sensitive to outliers. Therefore, robust estimators are employed to avoid the problems. Furthermore, the longitudinal data analysis is applied to examine whether betas over time and securities are the valid measure of risk in the CAPM. An empirical study is carried out to present the different approaches. We use the data about the Information and Electronic industry in Taiwan stock market during the period from September 1998 to December 2001. For the time series regression analysis, the robust methods lead to more explanatory power than the OLS results. The linear mixed-effect model is used to examine the effects of different streams and companies for the security excess returns in these data. 長期資料分析線性混和效應模型穩健估計最小削減平方法資本資產定價模型 longitudinal data analysis linear mixed-effects model robust estimation least trimmed squares estimator capital asset pricing model panel data analysis
36	資本資產定價模型與三因子模型之分析與比較 / Some Aspects about the Capital Asset Pricing Model and Three-factor Model 廖士仁, Liao, Shih-Jen Unknown Date (has links) 資本資產定價模型已被廣泛使用於分析股票風險與要求報酬率之間的關係。然而，個別股票風險Beta是否足以解釋其報酬，也受到愈來愈多的質疑。Fama和French在1993年提出額外兩個因子來解釋股票報酬。我們將應用資本資產定價模型和三因子模型來分析1963年7月至2002年12月之美國的三大股票交易所上市公司。藉由一次改變分析過程中的一部分，以觀察參數估計值是否穩定。結果發現Beta_HML總是顯著且最為穩定，而Beta_SMB並不顯著。Beta經常顯著，但變動情況較大。另外，我們將考慮個別股票本身的變異，亦即將隨機效果納入考量。 / The Capital Asset Pricing Model (CAPM) has been widely used to analyze the relationship between risk and required rate of return on a stock, while it is doubted that individual stock's risk Beta has enough explanatory power for it's returns. Fama and French (1993) proposed two more factors to help explaining stock returns. We use the CAPM and the three-factor model to analyze listed companys in American stock exchanges, during the period from July 1963 to December 2002. We change part of the analyzing process a time to see if the estimates of the parameters are stable. The risk-premium Beta_HML is always significant and it performs most stable, while another risk-premium Beta_SMB is never significant. Beta is usually significant but it varies. Furthermore, we take within-stock variation into account, so random effects are considered. 資本資產定價模型三因子模型線性混合效應模型時間序列迴歸橫斷面迴歸 Capital Asset Pricing Model Three-factor Model linear mixed-effects model time-series regression cross-sectional regression
37	Dynamiques de connectivité cérébrale fonctionnelle associées aux fluctuations journalières des états affectifs Racicot, Jeanne 12 1900 (has links) Les affects, émotions et humeurs sont des processus complexes dont le fonctionnement précis échappe toujours à la neuroscience affective. Un récent mouvement des études IRMf s’est tourné vers la recherche d’effets aux niveaux inter- et intra-individuels en raison du manque d’applicabilité individuelle des résultats provenant de moyennes de groupes basées sur des données transversales. En particulier, la recherche intra-individuelle permet l’étude de liens directs entre l’affectivité et la connectivité chez de mêmes individus à travers le temps. De précédentes études en IRMf rapportent ce type associations chez un unique participant, notre objectif a été d’étudier les effets intra-individuels communs pour un groupe d’individus. Nous avons utilisé le jeu de données Day2day, composé de 40 à 50 sessions pour 6 participants, chaque session incluant des données d’IRMf au repos ainsi que d’auto-évaluations des états affectifs. Nous avons analysé la relation entre l’affectivité et la connectivité fonctionnelle entre des régions cérébrales précédemment liées aux émotions et affects à l’aide de régressions linéaires mixtes multivariées. Nos modèles ont isolé des patrons de connectivité communs et généralisables liés aux variations intra-individuelles de l’affectivité observées au cours de plusieurs semaines et mois. Ces modèles impliquaient particulièrement l’amygdale et l’insula. Nos résultats ouvrent la possibilité de reproduire de tels modèles sur des jeux de données plus larges ainsi qu’à évaluer l’hétérogénéité entre sujets au-delà des effets moyens. La caractérisation de tels processus neurobiologiques pourrait être d’une grande utilité en clinique comme biomarqueur transdiagnostique de l’état affectif ou potentielle cible thérapeutique. / Affects, emotions and moods are complex processes, the precise functioning of which still eludes affective neuroscience. A recent movement in fMRI has turned to research of effects at the inter- and intra-individual level in response to the lack of individual-level applicability of results from cross-sectional group mean studies. In particular, intra-individual research enables the study of direct links between affective states and underlying connectivity in individuals across time. Previous fMRI studies have described these associations in a single participant, our objective was to find shared intraindividual effects across multiple subjects. We have used the Day2day dataset, comprising 40 to 50 sessions for six participants, each session including data from resting-state fMRI scans and self-report measures of state affectivity. We have investigated the relationship between affectivity and connectivity in brain regions linked to emotions and affects using multivariate mixed linear analysis. Our models have isolated common and generalizable patterns of connectivity linked to variations in affectivity observed over multiple weeks and months. These models involved mainly the amygdala and insula. Our results incentivize the re-creation of such modelsin larger datasets, and to assess heterogeneity beyond group mean effects. The characterization of such neurobiological processes could be of great use in a clinical setting as a transdiagnostic biomarker or as a potential therapeutic target. neurosciences affectives intra-individuel connectivité cérébrale fonctionnelle affects humeurs émotions apprentissage machine régression linéaire à effets mixtes affective neuroscience intra-individual functional magnetic resonance imaging functional connectivity affect mood emotion machine learning linear mixed-effects regression
38	Multispectral imaging of Sphagnum canopies: measuring the spectral response of three indicator species to a fluctuating water table at Burns Bog Elves, Andrew 02 May 2022 (has links) Northern Canadian peatlands contain vast deposits of carbon. It is with growing urgency that we seek a better understanding of their assimilative capacity. Assimilative capacity and peat accumulation in raised bogs are linked to primary productivity of resident Sphagnum species. Understanding moisture-mediated photosynthesis of Sphagnum spp. is central to understanding peat production rates. The relationship between depth to water table fluctuation and spectral reflectance of Sphagnum moss was investigated using multispectral imaging at a recovering raised bog on the southwest coast of British Columbia, Canada. Burns Bog is a temperate oceanic ombrotrophic bog. Three ecohydrological indicator species of moss were chosen for monitoring: S. capillifolium, S. papillosum, and S. cuspidatum. Three spectral vegetation indices (SVIs) were used to characterize Sphagnum productivity: the normalized difference vegetation index 660, the chlorophyll index, and the photochemical reflectance index. In terms of spectral sensitivity and the appropriateness of SVIs to species and field setting, we found better performance for the normalized difference vegetation index 660 in the discrimination of moisture mediated species-specific reflectance signals. The role that spatiotemporal scale and spectral mixing can have on reflectance signal fidelity was tested. We were specifically interested in the relationship between changes in the local water table and Sphagnum reflectance response, and whether shifting between close spatial scales can affect the statistical strength of this relationship. We found a loss of statistical significance when shifting from the species-specific cm2 scale to the spectrally mixed dm2 scale. This spatiospectral uncoupling of the moisture mediated reflectance signal has implications for the accuracy and reliability of upscaling from plot based measurements. In terms of species-specific moisture mediated reflectance signals, we were able to effectively discriminate between the three indicator species of Sphagnum along the hummock-to-hollow gradient. We were also able to confirm Sphagnum productivity and growth outside of the vascular growing season, establishing clear patterns of reflectance correlated with changes in the local moisture regime. The strongest relationships for moisture mediated Sphagnum productivity were found in the hummock forming species S. capillifolium. Each indicator Sphagnum spp. of peat has distinct functional traits adapted to its preferred position along the ecohydrological gradient. We also discovered moisture mediated and species-specific reflectance phenologies. These phenospectral characteristics of Sphagnum can inform future monitoring work, including the creation of a regionally specific phenospectral library. It’s recommended that further close scale multispectral monitoring be carried out incorporating more species of moss, as well as invasive and upland species of concern. Pervasive vascular reflectance bias in remote sensing products has implications for the reliability of peatland modelling. Avoiding vascular bias, targeted spectral monitoring of Sphagnum indicator species provides a more reliable measure for the modelling of peatland productivity and carbon assimilation estimates. / Graduate peatland peatland restoration peatland monitoring peatland modelling peat peat moss multispectral multispectral imaging multicamera array multitemporal multiple linear regression linear mixed effects Sphagnum sphagna Sphagnum capillifolium Sphagnum papillosum Sphagnum cuspidatum spatiospectral uncoupling near-sensing remote sensing phenospectral phenology phenologies phenospectral bias phenospectral libraries carbon assimilation carbon dioxide carbon dynamics carbon emissions carbon geographies carbon mineralization carbon sequestration carbon source carbon sink carbon storage irrecoverable carbon climate forcing methane Ecological Restoration restoration ecology ecohydrology ecohydrological restoration hydrology ecohydrological gradients ecological integrity reflectance nature based solutions ombrotrophic moss raised peatland mires mires photochemical reflectance index normalized difference vegetation index chlorophyll index climate change climate forcing climate envelope climatope nonvascular vascular bias plant functional type plant functional types structure equation models spectral vegetation indices hummock hollow acrotelm catotelm diplotelmic biocrusts organic soil periodicity moisture deficit senescence rejuvenescence productivity photosynthesis light use efficiency photosynthetic function photosynthetically active radiation water table hydrology rewetting depth to water table landscape change landscape degradation peat subsidence Burns Bog
39	Birds, bats and arthropods in tropical agroforestry landscapes: Functional diversity, multitrophic interactions and crop yield Maas, Bea 20 November 2013 (has links) No description available. 630 birds bats arthropods multitrophic interactions agroforestry tropical landscape forest margin landscape functional diversity crop yield exclosure experiments experimental exclusion arthropod suppression avian predation ecosystem services mist netting point counts artificial plasticine caterpillar dummy experiment biological control monitoring mapping Lemon-bellied White-eye Grosbeak Starling Zosterops chloris Scissiostrum dubium Theobroma cacao cacao agroforestry cacao diseases cacao harvest cacao pests flying vertebrates aerial insectivores volant vertebrates logging breeding colony flower herbivory mesopredator release predatory insects ants spiders aphids Lepidoptera Coleoptera Lepidopteran larvae sustainable agriculture sustainable agroforestry management implications management recommendations applied managament extensive land use management landscape management conservation biodiversity-friendly dbh distance to forest forest proximity habitat conversion herbivory Indonesia insectivorous bats insectivorous birds invertebrates Central Sulawesi Napu valley leaf gleaning leaf herbivory pests insects phytophagous insects plant productivity remnant forest trees shade tree managament South-east Asia Paleotropics tropical landscape tree height landscape gradient local shade management Cacao Pod Borer Cherelle Wilt fruit abortion Helopeltis sulawesi deforestation habitat fragmentation land use intensification forest margin species critical decline predation experiment species-specific functions Southeast Asia biodiversity conservation mesopredators food security human welfare human well-being poverty alleviation poverty reduction smallholder cacao smallholder plantation cacao farmers sustainable cacao management landscape perspective landscape scale large scale field experiment long term field experiment human wellbeing economic importance economic value valuation ecosystem services landscape matrix yield quality yield quantity fruit productivity species identity species diversity species richness ecosystem functioning pesticide use chemical compounds complex food web tritrophic interactions wildlife-friendly rural livelihoods endangered bird species endangered bat species endemic endemic birds endemic bats beneficial impact IUCN Lore Lindu National Park bioindicator indicator species forest margin agricultural habitat agroforestry systems population density predation activity species activity cacao flower cacao pod Orthoptera linear mixed effect models Tukey Post Hoc Test AICc model selection generalized least squares restricted maximum likelihood model simplification species richness estimator species accumulation linear mixed-effects models Likelihood Ratio Test Maximum Likelihood nocturnal insects diurnal arthropods nocturnal arthropods diurnal insects landscape context Land- und Forstwirtschaft (PPN621302791)

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