1,721,287 research outputs found
Penalized canonical correlation analysis: unraveling the genetic background of complex diseases
Get PDFStatistical challenges in observational cohort studies
Get PDFFor over a century observational cohort studies have been used to study determinants of health and disease. Within a sample from the population, we can determine the relation between health outcomes (e.g. death) and a broad range of factors as genetic markers, environmental exposures, and lifestyle determinants. Observational cohort studies are effective tools to investigate determinants of health and disease. Importantly, in this type of study the researcher only observes and does not assign interventions or characteristics to the individuals in the sample drawn from the population of interest. In this thesis, four subjects regarding the design and execution of cohort studies have been investigated. The first part is dedicated to problems that arise when our goal is to recruit a specific sample from a finite population. In the second part we propose methods to analyze of data derived from record linkage. In the third part we consider joint models with a large number of (recurrent) events and markers. Finally, in the fourth part, we analyzed childhood growth data from a large prospective cohort study
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Statistical analysis of repeated outcomes of different types
Get PDFThis thesis focused on analyzing data with multiple outcome variables. The motivating data sets comprised longitudinal markers of patients’ disease state (e.g. B cells and CD4+ T cell) as well as information on the time to an event (e.g. death) or (multiple) recurrent event times (e.g. repeated bacterial and viral infections). It was interesting to study how these markers relate with the event times and how their updated values may change prognosis. This could help to guide decision making for patient care. In part I we applied joint modeling to study the association between longitudinal and survival data. We also performed dynamic predictions of survival probabilities for a new subject, using marker values that were accrued overtime. We present an extension of the application of joint modelling to a setting with multiple markers and multi-type recurring events. In part II we applied landmarking as an alternative to joint modelling for performing dynamic predictions of survival probabilities. Landmarking circumvents possible computational complications of fitting time-dependent covariates, making it easier to compute survival probabilities compared to using joint models. We present an extension of the application of landmarking to a setting with recurring events of the same type. In part III we focused on validating prediction models in the presence of multiply imputed data. It was unclear how resampling should be performed over the imputed data sets when internal model validation was performed via bootstrap resampling. We investigated four ways of handling the multiply imputed data sets in the validation procedure
On multivariate statistical methods for omics data analysis
Get PDFIn biomedical research, it has become common to collect data that measures biological functions in different biological levels of an organism. On the biomolecular level, this means that cells and tissues can be described by data gathered from different biomolecular domains, such as by data from the genome, transcriptome or proteome. By collecting such multi modular data, it is hoped that biological processes in cells and tissues can be better modeled and understood. Ultimately, this knowledge can help to better understand health and disease in the whole organism itself. This thesis discusses some of the statistical methods that aim to integrate this type of multi modular biomolecular data
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Statistical modelling of repeated and multivariate survival data
Get PDFThe emphasis of this thesis lies on complex survival data and on the modelling of this kind of data. Statistical models are developed or adapted and applied to five different real data sets, which all contain repeated censored measurements. To take into account the correlation between these repeated data, a frailty is considered in all statistical analysis used. Extensions of and alternatives for frailty models are considered. The centre-effect on survival after bone marrow transplantation is studied in chapter 2. Models that are able to take into account a time-dependent frailty are proposed and compared. In chapter 3 survival analysis approaches are used for modelling an ecological capture-recapture data set. In chapter 4, the emphasis lies on the frailty model used in a genetic context. Our model is applied on age at onset of Huntington disease. Chapter 5 concerns the estimation of the correlation between processes with frailties. The approach is applied on the Dutch part of the data set from the Caprie trial, involving cardiac, cerebral and peripheral atherosclerosis. In chapter 6, the point of interest is the marginal survivor curve in different simulated balanced and unbalanced longitudinal situations. Finally, in chapter 7 a general summary can be found.UBL - phd migration 201
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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