1,720,962 research outputs found
The Generalized Lindley-Weibull Distribution with Applications to Lifetime Data
No full textA new class of distribution called the generalized Lindley-Weibull distribution for modeling lifetime data is proposed. This model further generalizes the Lindley distribution and allows for hazard rate functions that are monotonically decreasing, monotonically increasing bathtub and upside down bathtub shaped. The model provides a better fit to data in the sense that it leads to more accurate results and prediction, which should facilitate better public policy in a wide range of areas including but not limited to medicine and environmental health, genetics, reliability, survival analysis and time-to event data analysis. A comprehensive investigation and account of the mathematical and statistical properties and those of its sub models including estimation, and simulation issues are presented. Entropy which measures the variation of the uncertainty in a model and Fisher information are presented. Estimates of model parameters are obtained and some applications as well as numerical examples given. Estimates of sub models parameters are also determined from samples with type I right and type II doubly censored data. Real data examples are presented to illustrate the usefulness of these class of distributions
Advances in Spatiotemporal Modeling of Count Data With Application to COVID-19 Health Outcomes
No full textCOVID-19 has created a global health crisis since its emergence in late 2019. According to the Centers for Disease Control and Prevention (CDC), there have been over 104 million cases and 1.13 million deaths reported in the United States (US) as of June 2023. COVID-19 data are complex and present a number of statistical challenges that must be addressed to ensure valid inferences. These challenges include overdispersion of case and death counts, modeling of complex health effects, and zero-inflation. This dissertation proposes three aims to address these challenges: In Aim 1, we develop a Bayesian negative binomial regression model with spatially varying dispersion. This aim extends existing methods to address the issue of spatial heterogeneity and varying degrees of overdispersion in COVID-19 incidence data across counties. Using a simulation study, we demonstrate that ignoring heterogeneity in dispersion can lead to biased and inefficient estimation. For illustration, we apply the model to study the effect of social vulnerability index (SVI) on COVID-19 incidence from March 15 to December 31, 2020 in the state of Georgia. In Aim 2, we extend the current methods for continuous outcomes in environmental health mixture studies to count settings and develop a negative binomial Bayesian kernel machine regression (BKMR) method to model complex exposure-response associations involving count outcomes. Using a simulation study, we evaluate the performance of the proposed method in estimating the exposure-response function and identifying the most relevant mixture components. We apply the proposed method in modeling the joint effect of the social vulnerability index (SVI) variables on COVID-19 deaths from January 1 to December 31, 2021 in South Carolina. In Aim 3, we extend marginalized zero-inflated models to spatial setting and develop a marginalized zero-inflated negative binomial model for spatial data. In addition to capturing zero-inflation, the proposed method allows for direct modeling of the marginal mean, which is often the target of interest in public health and disease mapping studies involving zero-inflated data. We conduct simulation studies to investigate the features of the model and use the model to examine predictors of COVID-19 deaths in the US state of Georgia for the 2021 calendar year
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
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
The Log-Generalized Lindley-Weibull Distribution with Applications
Get PDFA new distribution called the log generalized Lindley-Weibull (LGLW) distribution for modeling lifetime data is proposed. This model further generalizes the Lindley distribution and allows for hazard rate functions that are monotonically decreasing, monotonically increasing and bathtub shaped. A comprehensive investigation and account of the mathematical and statistical properties including moments, moment generating function, simulation issues and entropy are presented. Estimates of model parameters via the method of maximum likelihood are given. Real data examples are presented to illustrate the usefulness and applicability of this new distribution
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
Optimal Trees for Functions of Internal Distance
No full textThe sum of distances between vertices of a tree has been considered from many aspects. The question of characterizing the extremal trees that maximize or minimize various such “distance-based” graph invariants has been extensively studied. Such invariants include, to name a few, the sum of distances between all pairs of vertices and the sum of distances between all pairs of leaves. With respect to the distances between internal vertices, we provide analogous results that characterize the extremal trees that minimize the value of any nonnegative and nondecreasing function of internal distances among trees with various constraints
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
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