1,721,137 research outputs found
Causal mediation analysis with failure time outcome and error-prone longitudinal covariate
Full text linkThesis (Ph.D.)--University of Washington, 2014Mediation analyses are important for understanding the biological mechanisms whereby a treatment/exposure influences an outcome of interest. For example, one may be interested in whether body fat accumulation mediates an association of certain dietary patterns with cancer risk. Similarly mediation analyses may aim to achieve an understanding of which elements of a multi-faceted dietary modification intervention were most influential in affecting disease incidence. Several challenges occur in mediation analysis: (1) the longitudinal and observational nature of the dietary variables and BMI/weight; (2) the measurement error in dietary variables which are often assessed using food frequency questionnaires; (3) control of measured/unmeasured confounders. In this dissertation, we proposed a general potential outcome framework for causal mediation analysis with failure time outcome and longitudinal mediator/exposure with measurement error. We proposed a method to correct for the systematic bias in longitudinal self-reported dietary data and use the calibrated data to estimate parameters in the survival model. We also proposed a robust estimator of key survival model parameters that can accommodate the existence of certain types of unmeasured confounders. We studied the performance of regression calibration methods for multiple choices of survival models numerically. We analyzed some important epidemiologic data and provided scientific information on the interplay between dietary exposures, physical activity and BMI in relation to site-specific cancer and other chronic diseases
Covariate Measurement Error Correction Methods in Mediation Analysis with Failure Time Data
Full text linkThesis (Ph.D.)--University of Washington, 2012Mediation analysis is important in understanding the mechanisms of one variable causing changes in another. Measurement error could be obscuring the ability of the potential mediator to explain this mechanism. Existing correction methods in mediation analysis literature are not directly applicable to failure time data. This dissertation focuses on developing correction methods for measurement error in the potential mediator with time-to-event outcome. We consider two specifications of measurement errors: one with technical measurement error only, and one with both technical measurement error and temporal variation. The underlying model with the true mediator values is assumed to be the Cox proportional hazards model. The hazard function induced by the observed mediator value no longer corresponds to a simple partial likelihood independent of the baseline hazard function, due to the conditioning event {T>=t}. We propose a mean-variance regression calibration and a follow-up time calibration approach to approximate the induced partial likelihood. Both methods demonstrate successes in recovering treatment effect estimates with both types of measurement error in simulation studies. Variance estimators are derived for both approaches. These two methods can be generalized to multiple biomarkers and case-cohort design. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of biomarker IGFBP4 in the relationship between hormone therapy and stroke
R-squared inference under non-normal error
No full textThesis (Ph.D.)--University of Washington, 2014Assessment of the relationship between diet and health status, especially association between diet and chronic disease risk, has attracted lot of research interest in statistical and epidemiologic studies. However, due to measurement errors in commonly utilized self-reported assessment approaches, an expected strong relationship was not identified in most studies. Developments in biomarker measures provide objective consumption assessment for specific dietary components which are utilized to develop calibrated dietary consumption function to remove bias embedded in those self-reported dietary measures. Researchers are interested in the explanatory strength of calibration equations and comparison of the strengths among various self-report measures. Thus, as a common metric used in these studies, reliable estimation of R-squared and of its confidence interval are important. Inference for R-squared, including confidence intervals for R-squared has not attracted much attention in the statistical literature. In this dissertation we proposed two methods to estimate confidence intervals for R-squared under errors from normal and non-normal distributions: the first method is based on asymptotic theories and entails the development of the asymptotic distribution of R-squared, and its relevant functions, when sample size becomes large; the second approach is based on a general F-test applied to linear regression but adjusts degree of freedom parameters in the F-test statistics using the empirical skewness and kurtosis of regression errors. In addition, when there are measurement errors in the independent variables, R-squared directly estimated from the regression can be biased and may, for example, underestimate the relationship between dependent and independent variables even with normally distributed errors. This dissertation also proposes a correction methodology to reduce the bias in R-squared estimation in the presence of classical additive measurement errors. The proposed methodologies have been evaluated in simulation and applied to nutritional biomarker studies in the Women's Health Initiative
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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