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Thèses sur le sujet « Longitudinal data analysi »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 19 juillet 2025

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1

LIU, XIAOQIU. "Managing Cardiovascular Risk in Hypertension: Methodological Issues in Blood Pressure Data Analysis." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/154475.

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Hypertension remains in 2017 a leading cause of mortality and disability worldwide. A number of issues related to the determinants of cardiovascular risk in hypertensive patients and to the strategies for better hypertension control are still pending. In such a context, aims of my research program were: 1. To investigate the contribution of blood pressure variability to the risk of cardiovascular mortality in hypertensive patients. In this setting, different methods for assessing blood pressure variability and different models exploring the link between blood pressure variability and outcome

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Petzold, Max. "Evaluation of information in longitudinal data." Göteborg : Statistical Research Unit, Göteborg University, 2003. http://catalog.hathitrust.org/api/volumes/oclc/52551306.html.

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3

Yao, Fang. "Functional data analysis for longitudinal data /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2003. http://uclibs.org/PID/11984.

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4

Sort, Lucas. "Development of new statistical approaches for the investigation of multiblock and tensor longitudinal data." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG001.

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En recherche médicale, les données sont devenues de plus en plus complexes au cours des dernières décennies. En effet, les données sont désormais souvent observées à différentes occasions au cours du temps pour permettre un meilleur suivi de l'évolution des processus biologiques ayant un intérêt d'ordre médical. Dans ce contexte, ces données, souvent nommées données longitudinales, possèdent fréquemment une structure complexe de dimension élevée. Par exemple, dans un nombre croissant de situations, les données peuvent être structurées en un tableau multidimensionnel, également appelé tenseur.

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5

Zhu, Liang. "Semiparametric analysis of multivariate longitudinal data." Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/6044.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2008.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 3, 2009) Vita. Includes bibliographical references.

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Mills, Joanna E. "The analysis longitudinal binary data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ57350.pdf.

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7

Fullwood, Catherine Lee. "Longitudinal analysis of anticoagulent data." Thesis, Lancaster University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431469.

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8

Bai, Yang, and 柏楊. "Statistical analysis for longitudinal data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42841756.

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Bai, Yang. "Statistical analysis for longitudinal data." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B42841756.

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10

Kim, Yangjin. "Statistical analysis of longitudinal data /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3100054.

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11

Modur, Sharada P. "Missing Data Methods for Clustered Longitudinal Data." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1274876785.

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12

Boudreau, Christian. "Duration data analysis in longitudinal surveys." Waterloo, Ont. : University of Waterloo, 2003. http://etd.uwaterloo.ca/etd/cboudrea2003.pdf.

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Thesis (Ph.D.)--University of Waterloo, 2003.<br>"A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Statistics". Includes bibliographical references. Also available in microfiche format.

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13

Boudreau, Christian. "Duration Data Analysis in Longitudinal Survey." Thesis, University of Waterloo, 2003. http://hdl.handle.net/10012/1043.

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Considerable amounts of event history data are collected through longitudinal surveys. These surveys have many particularities or features that are the results of the dynamic nature of the population under study and of the fact that data collected through longitudinal surveys involve the use of complex survey designs, with clustering and stratification. These particularities include: attrition, seam-effect, censoring, left-truncation and complications in the variance estimation due to the use of complex survey designs. This thesis focuses on the last two points. Statistical methods

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14

Ricci, Peter J. "Some aspects of longitudinal data analysis /." Title page, contents and summary only, 1994. http://web4.library.adelaide.edu.au/theses/09PH/09phr491.pdf.

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15

Fear, Simon Charles. "The analysis of categorical longitudinal data." Thesis, University of Liverpool, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266052.

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16

Stern, Theresa Marie Papa. "Longitudinal analysis of incomplete binary data /." The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487947501135652.

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17

Gao, Dexiang. "Analysis of clustered longitudinal count data /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2007.

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Thesis (Ph.D. in Analytic Health Sciences, Department of Preventive Medicine and Biometrics) -- University of Colorado Denver, 2007.<br>Typescript. Includes bibliographical references (leaves 75-77). Free to UCD affiliates. Online version available via ProQuest Digital Dissertations;

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18

Schabenberger, Oliver. "The analysis of longitudinal ordinal data." Diss., This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-02272007-092413/.

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19

Cheung, Ka-yan, and 張嘉茵. "Multilevel modeling for the analysis of longitudinal periodontal data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46605496.

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20

Jiang, Xiaoping. "Nonparametric quasi-likelihood in longitudinal data analysis." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/2078.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2004.<br>Thesis research directed by: Mathematical Statistics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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21

Li, Zuojing. "Longitudinal data analysis using generalized linear models." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27267.

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In this work we examine various conditions under which the usual asymptotic results (i.e. the weak consistency, the asymptotic normality and the strong consistency) hold for the regressor parameter beta which arises in a linear model (Chapter 2), a generalized linea model (GLM) with a fully specified likelihood (Chapter 3) or as a root of the generalized estimating equation (GEE) associated with a sequence of longitudinal observations (Chapter 4). Our main references for each of these chapters are [12], [9], respectively [20]. We provide detailed proofs of the results found in the above-mentio

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22

Green, Brittany. "Ultra-high Dimensional Semiparametric Longitudinal Data Analysis." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1593171378846243.

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23

Zhao, Rui. "Integrated Analysis of Longitudinal Tumor Burden Data." Thesis, Harvard University, 2014. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14226076.

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The first part of this thesis introduces a new statistical method to estimate parameter values in a mixed population consisting of both single- and bi- phasic longitudinal trajectories. This pro- posed model is capable of categorizing patients according to their longitudinal relationships and estimating the associated parameters of interest, while accounting for between-patient variability. We applied this method to a large phase III randomized trial and found significant differences in patients between different treatment cohorts and within the same treatment cohort, in terms of their longitu

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24

Khatiwada, Aastha. "Multilevel Models for Longitudinal Data." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3090.

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Longitudinal data arise when individuals are measured several times during an ob- servation period and thus the data for each individual are not independent. There are several ways of analyzing longitudinal data when different treatments are com- pared. Multilevel models are used to analyze data that are clustered in some way. In this work, multilevel models are used to analyze longitudinal data from a case study. Results from other more commonly used methods are compared to multilevel models. Also, comparison in output between two software, SAS and R, is done. Finally a method consisting of f

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25

Chang, Janis. "Analysis of ordered categorical data." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27857.

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Methods of testing for a location shift between two populations in a longitudinal study are investigated when the data of interest are ordered, categorical and non-linear. A non-standard analysis involving modelling of data over time with transition probability matrices is discussed. Next, the relative efficiencies of statistics more frequently used for the analysis of such categorical data at a single time point are examined. The Wilcoxon rank sum, McCullagh, and 2 sample t statistic are compared for the analysis of such cross sectional data using simulation and efficacy calculations. Simulat

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26

Fatima, Kaniz. "Analysis of longitudinal data with ordered categorical response." Thesis, University of Reading, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239058.

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27

Hu, Zonghui. "Semiparametric functional data analysis for longitudinal/clustered data: theory and application." Texas A&M University, 2004. http://hdl.handle.net/1969.1/3088.

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Semiparametric models play important roles in the ﬁeld of biological statistics. In this dissertation, two types of semiparametic models are to be studied. One is the partially linear model, where the parametric part is a linear function. We are to investigate the two common estimation methods for the partially linear models when the data is correlated Â longitudinal or clustered. The other is a semiparametric model where a latent covariate is incorporated in a mixed effects model. We will propose a semiparametric approach for estimation of this model and apply it to the study on colon

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28

Barry, Sarah Jane Elizabeth. "Longitudinal analysis of three-dimensional facial shape data." Connect to e-thesis, 2008. http://theses.gla.ac.uk/190/.

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Thesis (Ph.D.) - University of Glasgow, 2008.<br>Ph.D. thesis submitted to the Faculty of Information and Mathematical Sciences, Department of Statistics, University of Glasgow, 2008. Includes bibliographical references. Print version also available.

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29

Barry, Sarah J. E. "Longitudinal analysis of three-dimensional facial shape data." Thesis, University of Glasgow, 2008. http://theses.gla.ac.uk/190/.

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Shape data encompass all the information that is left to describe a shape following removal of location, rotation and scale effects. Much work has been done in the analysis of two-dimensional shapes depicted by anatomical landmarks placed at points of importance. Less has been carried out in the area of three-dimensional shapes, particularly in terms of growth or change over time. This thesis considers the analysis of such longitudinal three-dimensional shape data. In doing so, two well established but normally unrelated areas of Statistics are brought together: those of longitudinal data anal

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30

Verzilli, Claudio John. "Methods for the analysis of incomplete longitudinal data." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2003. http://researchonline.lshtm.ac.uk/4646517/.

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Unplanned missing data commonly arise in longitudinal trials. When the mechanism driving the missing data process is related to the outcome under investigation, traditional methods of analysis may yield seriously biased parameter estimates. Motivated by data from two clinical trials, this thesis explores various approaches to dealing with data incompleteness. In the first part, a Monte Carlo EM algorithm is developed and used to fit so called random-co efficient-based dropout models; these models relate the probability of a patient's dropout in follow-up studies to some subject-specific charac

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31

Jangerstad, August. "Transcription factor analysis of longitudinal mRNA expression data." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278693.

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Transcription factors (TFs) are key regulatory proteins that regulate transcriptionthrough precise, but highly variable binding events to cis-regulatory elements.The complexity of their regulatory patterns makes it difficult to determinethe roles of different TFs, a task which the field is still struggling with.Experimental procedures for this purpose, such as knock out experiments, arehowever costly and time consuming, and with the ever-increasing availabilityof sequencing data, computational methods for inferring the activity of TFsfrom such data have become of great interest. Current method

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32

French, Benjamin. "Analysis of aggregate longitudinal data with time-dependent exposure /." Thesis, Connect to this title online; UW restricted, 2008. http://hdl.handle.net/1773/9569.

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33

Moore, Page Casey Seaman John Weldon. "A restriction method for the analysis of discrete longitudinal missing data." Waco, Tex. : Baylor University, 2006. http://hdl.handle.net/2104/4880.

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34

Fu, Bo, and 傅博. "Some topics in longitudinal data analysis and panel time seriesmodels." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B31244166.

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35

Kurland, Brenda F. "Analysis of binary longitudinal data with dropout and death /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/9593.

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36

Solis-Trapala, Ivonne Lissette. "Likelihood methods for the analysis of discrete longitudinal data." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615839.

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37

Duncombe, Alastair Richard. "Bayesian analysis of longitudinal data with non random dropout." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272133.

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38

Jaffrezic, Florence. "Statistical models for the genetic analysis of longitudinal data." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/12274.

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The first objective of this work was to compare and contrast different methodologies for genetic analysis. As the range of all possible models can be very large in practice, it is advisable to have a preliminary idea of the covariance structure of the data, and a non-parametric approach based on the variogram was proposed. It is especially adapted for exploratory analysis when a large number of observations is available per subject over time and was applied to the analysis of daily records for milk production in dairy cattle. Model comparisons in the univariate case showed that character proce

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39

Beaghen, Michael Jr. "Canonical Variate Analysis and Related Methods with Longitudinal Data." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/29840.

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Canonical variate analysis (CVA) is a widely used method for analyzing group structure in multivariate data. It is mathematically equivalent to a one-way multivariate analysis of variance and often goes by the name of canonical discriminant analysis. Change over time is a central feature of many phenomena of interest to researchers. This dissertation extends CVA to longitudinal data. It develops models whose purpose is to determine what is changing and what is not changing in the group structure. Three approaches are taken: a maximum likelihood approach, a least squares approach, and a covaria

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Tharu, Bhikhari Prasad. "Statistical Analysis and Modeling Health Data: A Longitudinal Study." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6413.

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Lung cancer has been considered one of the leading causes of deaths while cancer re- mains the second most common cause of deaths in the USA. Understanding the behavior of a disease over time could yield important information to make decisions about the disease. Statistical models could provide crucial clues and help to make a decision about the dis- ease, budget allocation, evaluation, and implement prevention. Longitudinal trend analysis of the diseases helps to understand long term effects and nature. Cholesterol level is one of the most contributing risk factors for Coronary Heart Disease.

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Rajeev, Deepthi. "Separate and Joint Analysis of Longitudinal and Survival Data." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1775.pdf.

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42

Rogers-McMillan, Sarah. "Diminishing egocentricity: a secondary analysis of longitudinal adolescent data." Thesis, Boston University, 2009. https://hdl.handle.net/2144/32000.

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Thesis (Ed.D.)--Boston University<br>PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.<br>This study attempts to demonstrate the process of diminishing egocentricity, which appears to be central to the individual's evolving capacity to be in relation to the other, in the developing early-to-middle

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Hu, Shuwen. "Statistical modeling and machine learning in longitudinal data analysis." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/211253/1/Shuwen_Hu_Thesis.pdf.

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This thesis mainly concerns the statistical modelling and machine learning methods for the analysis of longitudinal data. As a contribution to this area, this thesis provides theoretical discussion and empirical illustrations of longitudinal data analysis. The first contribution is developing methods to obtain robust and efficient variance estimators when the cluster size is large. The second one is comparing a traditional parametric approach, the linear mixed model with machine learning methods in longitudinal data analysis. The last one is extracting new features to improve sheep behaviour c

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Chang, Shu-Ching. "Antedependence Models for Skewed Continuous Longitudinal Data." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/4827.

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This thesis explores the problems of fitting antedependence (AD) models and partial antecorrelation (PAC) models to continuous non-Gaussian longitudinal data. AD models impose certain conditional independence relations among the measurements within each subject, while PAC models characterize the partial correlation relations. The models are parsimonious and useful for data exhibiting time-dependent correlations. Since the relation of conditional independence among variables is rather restrictive, we first consider an autoregressively

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Rocha, Everton Batista da. "Modelos para a análise de dados de contagens longitudinais com superdispersão: estimação INLA." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-05112015-144057/.

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Em ensaios clínicos é muito comum a ocorrência de dados longitudinais discretos. Para sua análise é necessário levar em consideração que dados observados na mesma unidade experimental ao longo do tempo possam ser correlacionados. Além dessa correlação inerente aos dados é comum ocorrer o fenômeno de superdispersão (ou sobredispersão), em que, existe uma variabilidade nos dados além daquela captada pelo modelo. Um caso que pode acarretar a superdispersão é o excesso de zeros, podendo também a superdispersão ocorrer em valores não nulos, ou ainda, em ambos os casos. Molenberghs, Verbeke e Demétr

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Cao, Yu. "Bayesian nonparametric analysis of longitudinal data with non-ignorable non-monotone missingness." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5750.

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In longitudinal studies, outcomes are measured repeatedly over time, but in reality clinical studies are full of missing data points of monotone and non-monotone nature. Often this missingness is related to the unobserved data so that it is non-ignorable. In such context, pattern-mixture model (PMM) is one popular tool to analyze the joint distribution of outcome and missingness patterns. Then the unobserved outcomes are imputed using the distribution of observed outcomes, conditioned on missing patterns. However, the existing methods suffer from model identification issues if data is sparse

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O'Keeffe, Aidan Gerard. "Causal inference and dynamic modelling in the analysis of longitudinal data." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609903.

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Park, Jeanseong. "Longitudinal Data Analysis Using Generalized Linear Model with Missing Responses." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33355.

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Longitudinal studies rely on data collected at several occasions from a set of selected individuals. The purpose of these studies is to use a regression-type model to express a response variable as a function of explanatory variables, or covariates. In this thesis, we use marginal models for the analysis of such data, which, coupled with the method of estimating equations, provide estimators of the main regression parameter. When some of the responses are missing or there is error in the recorded covariates, the original estimating equation may be biased. We use techniques available in the lit

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Tchatchueng, Mbougua Jules Brice. "Problématiques statistiques rencontrées dans l’étude du traitement antirétroviral des adultes infectés par le VIH en Afrique subsaharienne." Thesis, Montpellier 1, 2012. http://www.theses.fr/2012MON1T006/document.

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Partant de problématiques statistiques rencontrées dans l'étude du traitement antirétroviral des adultes infectés par le virus de l'immunodéficience humaine (VIH) en Afrique subsaharienne, cette thèse cherche, d'une part, à favoriser la vulgarisation d'outils méthodologiques relativement récents auprès d'un public d'utilisateurs moins avertis et, d'autre part, à participer au développement de nouveaux outils. Le premier chapitre présente différentes méthodes de modélisation des données longitudinales dont des méthodes d'analyse de l'évolution d'un critère au cours du temps (les modèles linéair

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Kohlmann, Mareike. "Discriminant Analysis for Longitudinal Data with Application in Medical Diagnostics." Diss., lmu, 2010. http://nbn-resolving.de/urn:nbn:de:bvb:19-127645.

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