1,720,976 research outputs found
Semiparametric Regression Analysis of Panel Count Data: A Practical Review
Full text linkPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149207/1/insr12271_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149207/2/insr12271.pd
Weighted Accelerated Failure Time Models and Their Applications In Clustered Data
No full textIn survival analysis, semiparametric accelerated failure time (AFT) model postulates a
log-linear model for the failure times and covariates with an unspecified error, which is a
very useful alternative to proportional hazard model. Clustered failure time data often
arise from biomedical research. There are several challenges in modeling the clustered
failure time distribution: within-cluster dependency, right censoring, and the unknown
relationship between covariates and failure times. In this dissertation, we propose a
new estimation method, weighted least-squares approach, for the semiparametric AFT
model to estimate the parameters of interest for mixture cure data and case-cohort
data, separately. The weighted least-squares approach is not only very intuitive but
also can be easily extend to clustered data by incorporating generalized estimating
equation (GEE).
Currently, there are about 5.6 million people in America are suffering from Alzheimer’s
disease (AD). Unfortunately, AD has no current cure. Mouse memory study is carried
out to better understand the pathogenesis of AD. Based on the data structure analysis
of mouse memory data, we propose weighted least-squares approach to semiparametric
AFT mixture cure model to estimate the cured rate of treatment and the failure time
distribution at the same time in Chapter 2. It is further extended to clustered data by
taking within-cluster dependency into account through GEE. Large scale simulations
are conducted to investigate the properties of the proposed estimators. The proposed
method is applied to mouse memory data to investigate the effect of specific gene
expressions on mouse memory.
In the biomedical research, two analysis challenges often arise. The first challenge is
that some main covariates of interest are time consuming or very expensive to measure;
the second challenge is that the outcome in the data set is rare. In Chapter 3, weighted
least-squares approach is proposed to semiparametric AFT model for case-cohort design
where inverse probability weights (IPW) is used to correct the sampling bias. It is
also extended to clustered case-cohort data where the within-cluster dependency is
accounted for by GEE. The performance of the proposed model is evaluated by large
scale simulations. An application to a retrospective dental study is conducted
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
Statistical Methods and Computing for Semiparametric Accelerated Failure Time Model with Induced Smoothing
No full textIn survival analysis, semiparametric accelerated failure time (AFT) models directly relate the predicted failure times to covariates and are a useful alternative to relative risk models. Recent developments in rank-based estimation and least squares estimation provide promising tools to make the AFT models more attractive in practice. In this dissertation, we propose fast and accurate inferences for AFT models with applications under various sampling schemes.
The challenge in computing the rank-based estimator comes from solving nonsmooth estimating equations. This difficulty can be overcome with an induced smoothing approach. We generalize the induced smoothing approach to incorporate weights with missing data arising from case-cohort study and stratified sampling design. Parameters are estimated with smoothed estimating equations. Variance estimators are obtained through efficient resampling methods that avoid full blown bootstrap. The estimator from the smooth weighted estimating equations are shown to be consistent and have the same asymptotic distribution as that from the nonsmooth version. An univariate failure time data from a tumor study and a clustered data from a dental study are analyzed.
The induced smoothing approach for rank-based AFT models is natural with Gehan\u27s weight. Using the estimator from induced smoothing with Gehan\u27s weight as an initial value, we propose an iterative procedure that works for any weight of general form. The resulting estimator has the same asymptotic properties as the nonsmooth rank-based estimator with the same weight. Real data from an adolescent stress duration study and a case-cohort study for Wilm\u27s tumor illustrate the methods.
As for the least square estimation, we propose a generalized estimating equations (GEE) approach. The consistency of the regression coefficient estimator is robust to misspecification of working covariance and the efficiency is higher when the working covariance structure is closer to the truth. The marginal error distributions and regression coefficient are allowed be unique for each margin or partially shared across margins as needed. The resulting estimator is consistent and asymptotically normal, with variance estimated through a multiplier resampling method. Bivariate failure times data from a diabetic retinopathy study is analyzed.
All the aforementioned methods for AFT models are implemented in an R package aftgee (http://cran.r-project.org/web/packages/aftgee/index.html)
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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