Relevant bibliographies by topics / Generalised estimating equations (GEE)

Academic literature on the topic 'Generalised estimating equations (GEE)'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Generalised estimating equations (GEE)"

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Vens, M., and A. Ziegler. "Generalized Estimating Equations." Methods of Information in Medicine 49, no. 05 (2010): 421–25. http://dx.doi.org/10.3414/me10-01-0026.

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Summary Background: Generalized estimating equations (GEE) are an extension of generalized linear models (GLM) in that they allow adjusting for correlations between observations. A major strength of GEE is that they do not require the correct specification of the multivariate distribution but only of the mean structure. Objectives: Several concerns have been raised about the validity of GEE when applied to dichotomous dependent variables. In this contribution, we summarize the theoretical findings concerning efficiency and validity of GEE. Methods: We introduce the GEE in a formal way, summarize general findings on the choice of the working correlation matrix, and show the existence of a dilemma for the optimal choice of the working correlation matrix for dichotomous dependent variables. Results: Biological and statistical arguments for choosing a specific working correlation matrix are given. Three approaches are described for overcoming the range restriction of the correlation coefficient. Conclusions: The three approaches described in this article for overcoming the range restrictions for dichotomous dependent variables in GEE models provide a simple and practical way for use in applications.
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Hidayati, Rizka Dwi, I. Made Tirta, and Yuliani Setia Dewi. "The Efficiency of First (GEE1) and Second (GEE2) Order “Generalized Estimating Equations” for Longitudinal Data." Jurnal ILMU DASAR 15, no. 1 (August 7, 2014): 29. http://dx.doi.org/10.19184/jid.v15i1.553.

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The approach of GEE focuses on a linear model for the mean of the observations in the cluster without full specification the distribution of full-on observation. GEE is a marginal model where is not based on the full likelihood of the response, but only based on the relationship between the mean (first moment) and variance (second moment) as well as the correlation matrix. The advantage of GEE is that the mean of parameter are estimated consistently regardless whether the correlation structure is specified correctly or not, as long as the mean has the correct specifications. However, the efficiency may be reduced when the working correlation structure is wrong. GEE was designed to focus on the marginal mean and correlation structure as nuisiance treat. Implementation of GEE is usually limited to the number of working correlation structure (eg AR-1, exchangeable, independent, m-dependent and unstructured). To increase the efficiency of the GEE, has introduced a variation called the Generalized Estimating Equations order 2 (GEE2). GEE2 has been introduced to overcome the problem that considers correlation GEE as nuisiance, by applying the second equation to estimate covariance parameters and solved simultaneously with the first equation. This study used simulation data which are designed based on the the AR-1 and Exchangeable correlation structure, then estimation are done using theAR1 and exchangeable. For GEE2, estimation done by adding model for correlation link. The result is a link affects the efficiency of the model correlation is shown with standard error values ​​generated by GEE2 method is smaller than the GEE method.
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Lo, Chi Ho, Wing Kam Fung, and Zhong Yi Zhu. "Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models." ASTIN Bulletin 37, no. 02 (November 2007): 323–43. http://dx.doi.org/10.2143/ast.37.2.2024070.

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A generalized estimating equations (GEE) approach is developed to estimate structural parameters of a regression credibility model with independent or moving average errors. A comprehensive account is given to illustrate how GEE estimators are worked out within an extended Hachemeister (1975) framework. Evidenced by results of simulation studies, the proposed GEE estimators appear to outperform those given by Hachemeister, and have led to a remarkable improvement in accuracy of the credibility estimators so constructed.
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Lo, Chi Ho, Wing Kam Fung, and Zhong Yi Zhu. "Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models." ASTIN Bulletin 37, no. 2 (November 2007): 323–43. http://dx.doi.org/10.1017/s0515036100014896.

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A generalized estimating equations (GEE) approach is developed to estimate structural parameters of a regression credibility model with independent or moving average errors. A comprehensive account is given to illustrate how GEE estimators are worked out within an extended Hachemeister (1975) framework. Evidenced by results of simulation studies, the proposed GEE estimators appear to outperform those given by Hachemeister, and have led to a remarkable improvement in accuracy of the credibility estimators so constructed.
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Lange, Christoph, and John C. Whittaker. "Mapping Quantitative Trait Loci Using Generalized Estimating Equations." Genetics 159, no. 3 (November 1, 2001): 1325–37. http://dx.doi.org/10.1093/genetics/159.3.1325.

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AbstractA number of statistical methods are now available to map quantitative trait loci (QTL) relative to markers. However, no existing methodology can simultaneously map QTL for multiple nonnormal traits. In this article we rectify this deficiency by developing a QTL-mapping approach based on generalized estimating equations (GEE). Simulation experiments are used to illustrate the application of the GEE-based approach.
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Breitung, J., N. R. Chaganty, R. M. Daniel, M. G. Kenward, M. Lechner, P. Martus, R. T. Sabo, Y. G. Wang, and C. Zorn. "Discussion of “Generalized Estimating Equations: Notes on the Choice of the Working Correlation Matrix”." Methods of Information in Medicine 49, no. 05 (2010): 426–32. http://dx.doi.org/10.1055/s-0038-1625133.

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Summary Objective: To discuss generalized estimating equations as an extension of generalized linear models by commenting on the paper of Ziegler and Vens “Generalized Estimating Equations: Notes on the Choice of the Working Correlation Matrix”. Methods: Inviting an international group of experts to comment on this paper. Results: Several perspectives have been taken by the discussants. Econometricians have established parallels to the generalized method of moments (GMM). Statisticians discussed model assumptions and the aspect of missing data. Applied statisticians commented on practical aspects in data analysis. Conclusions: In general, careful modeling correlation is encouraged when considering estimation efficiency and other implications, and a comparison of choosing instruments in GMM and generalized estimating equations (GEE) would be worthwhile. Some theoretical drawbacks of GEE need to be further addressed and require careful analysis of data. This particularly applies to the situation when data are missing at random.
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Wang, Ming. "Generalized Estimating Equations in Longitudinal Data Analysis: A Review and Recent Developments." Advances in Statistics 2014 (December 1, 2014): 1–11. http://dx.doi.org/10.1155/2014/303728.

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Generalized Estimating Equation (GEE) is a marginal model popularly applied for longitudinal/clustered data analysis in clinical trials or biomedical studies. We provide a systematic review on GEE including basic concepts as well as several recent developments due to practical challenges in real applications. The topics including the selection of “working” correlation structure, sample size and power calculation, and the issue of informative cluster size are covered because these aspects play important roles in GEE utilization and its statistical inference. A brief summary and discussion of potential research interests regarding GEE are provided in the end.
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Feddag, Mohand-Larbi, Ion Grama, and Mounir Mesbah. "Generalized Estimating Equations (GEE) for Mixed Logistic Models." Communications in Statistics - Theory and Methods 32, no. 4 (January 4, 2003): 851–74. http://dx.doi.org/10.1081/sta-120018833.

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Ghisletta, Paolo, and Dario Spini. "An Introduction to Generalized Estimating Equations and an Application to Assess Selectivity Effects in a Longitudinal Study on Very Old Individuals." Journal of Educational and Behavioral Statistics 29, no. 4 (December 2004): 421–37. http://dx.doi.org/10.3102/10769986029004421.

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Correlated data are very common in the social sciences. Most common applications include longitudinal and hierarchically organized (or clustered) data. Generalized estimating equations (GEE) are a convenient and general approach to the analysis of several kinds of correlated data. The main advantage of GEE resides in the unbiased estimation of population-averaged regression coefficients despite possible misspecification of the correlation structure. This article aims to provide a concise, nonstatistical introduction to GEE. To illustrate the method, an analysis of selectivity effects in the Swiss Interdisciplinary Longitudinal Study on the Oldest Old is presented.
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Sahin, Fezan, Unal Ayranci, Setenay Oner, Canan Demirustu, Cengiz Bal, Ertugrul Colak, Cinar Yenilmez, Kazim Ozdamar, and Gulten Seber. "FACTORS INFLUENCING STUDENTS' SUCCESS: A GENERALIZED ESTIMATING EQUATIONS STUDY." Social Behavior and Personality: an international journal 35, no. 7 (January 1, 2007): 987–96. http://dx.doi.org/10.2224/sbp.2007.35.7.987.

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The goals of this study were to determine the factors influencing children's success according to Generalized Estimating Equations (GEE) through the Family Report Form (FRF; constituted by the authors), Teacher's Report Form (TRF; Achenbach, 1991b) and Child Behavior Check List (CBCL; Achenbach & Edelbrock, 1983), and to form a new and actual reference success form for Turkish children. The study sample included 4130 primary school children in Eskisehir, Turkey. School success was measured as the total scores that students achieved in the following classes: cultural, social, science, foreign language, computer, picture, music and job-occupation. The TRF, CBCL and FRF forms consist of the sum of subtests, which includes 9 factor scales, namely anxiety/depression, somatic complaints, social withdrawal, delinquent behavior, social problems, thought problems, attention deficits, aggressive behavior, and other. As the statistical analyses, GEE method, stepwise regression analysis and missing value analyses were used. The items that had the greatest negative effect on the students' success were “has poor school work” and “can't concentrate or can't pay attention for long”. On the other hand, the item that had the greatest positive effect on students' success was “feels he/she has to be perfect”. It may be recommended that students, their families, and teachers should be informed about factors influencing school success.
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Dissertations / Theses on the topic "Generalised estimating equations (GEE)"

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Diaz, Pedro, and Grant Skrepnek. "Marginal Tax Rates and Innovative Activity in the Biotech Sector." The University of Arizona, 2013. http://hdl.handle.net/10150/614244.

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Class of 2013 Abstract
Specific Aims: To assess the association between marginal tax rates (MTR) and innovative output of biotechnology firms. The MTR plays an important role in firms’ financing choices. Assessment of a firm’s tax status may reveal how firms decide on investment policies that affect R&D. Methods: A retrospective database analysis was used. Subjects included were firms within the biotechnology sector with the Standard Industrial Classification code of 2836 from 1980 - 2011. MTR Data was obtained from the S&P Compustat database, and Patent data was obtained from the U.S. Patent and Trademark Office. Changes in MTR’s on outcomes of patents were analyzed by performing an inferential analysis. Generalized estimating equations (GEE) were used, specifically utilizing a GEE regression with a negative binomial distributional family with log link, independent correlation structure and robust standard error variance calculation. Patents were regressed by the lagged change in MTR, after interest deductions. Main Results: The lag years 2 and 5 of the MTR change were statistically significant, (p = 0.031) and (p = 0.026) for each model respectively. Every one unit increase in the change of the MTRs was associated with large and significant drops in patents 78.8% (IRR = 0.212), 90.7% (IRR = 0.093), 92.7% (IRR = 0.073) at year 2 lag and 84.8% (IRR = 0.152), 92.6% (IRR = 0.074) at year 5 lag. Conclusion: An increase in the change of the MTR results in significant drops in patenting activity.
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Kauffman, Rudi D. "The Outcomes of Just War: An Empirical Study of the Outcomes Associated with Adherence to Just War Theory, 1960-2000." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342105770.

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Sagara, Issaka. "Méthodes d'analyse statistique pour données répétées dans les essais cliniques : intérêts et applications au paludisme." Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM5081/document.

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De nombreuses études cliniques ou interventions de lutte ont été faites ou sont en cours en Afrique pour la lutte contre le fléau du paludisme. En zone d'endémie, le paludisme est une maladie récurrente. La revue de littérature indique une application limitée des outils statistiques appropriés existants pour l'analyse des données récurrentes de paludisme. Nous avons mis en oeuvre des méthodes statistiques appropriées pour l'analyse des données répétées d'essais thérapeutiques de paludisme. Nous avons également étudié les mesures répétées d'hémoglobine lors du suivi de traitements antipaludiques en vue d'évaluer la tolérance ou sécurité des médicaments en regroupant les données de 13 essais cliniques.Pour l'analyse du nombre d'épisodes de paludisme, la régression binomiale négative a été mise en oeuvre. Pour modéliser la récurrence des épisodes de paludisme, quatre modèles ont été utilisés : i) Les équations d'estimation généralisées (GEE) utilisant la distribution de Poisson; et trois modèles qui sont une extension du modèle Cox: ii) le modèle de processus de comptage d'Andersen-Gill (AG-CP), iii) le modèle de processus de comptage de Prentice-Williams-Peterson (PWP-CP); et iv) le modèle de Fragilité partagée de distribution gamma. Pour l'analyse de sécurité, c'est-à-dire l'évaluation de l'impact de traitements antipaludiques sur le taux d'hémoglobine ou la survenue de l'anémie, les modèles linéaires et latents généralisés mixtes (« GLLAMM : generalized linear and latent mixed models ») ont été mis en oeuvre. Les perspectives sont l'élaboration de guides de bonnes pratiques de préparation et d'analyse ainsi que la création d'un entrepôt des données de paludisme
Numerous clinical studies or control interventions were done or are ongoing in Africa for malaria control. For an efficient control of this disease, the strategies should be closer to the reality of the field and the data should be analyzed appropriately. In endemic areas, malaria is a recurrent disease. Repeated malaria episodes are common in African. However, the literature review indicates a limited application of appropriate statistical tools for the analysis of recurrent malaria data. We implemented appropriate statistical methods for the analysis of these data We have also studied the repeated measurements of hemoglobin during malaria treatments follow-up in order to assess the safety of the study drugs by pooling data from 13 clinical trials.For the analysis of the number of malaria episodes, the negative binomial regression has been implemented. To model the recurrence of malaria episodes, four models were used: i) the generalized estimating equations (GEE) using the Poisson distribution; and three models that are an extension of the Cox model: ii) Andersen-Gill counting process (AG-CP), iii) Prentice-Williams-Peterson counting process (PWP-CP); and (iv) the shared gamma frailty model. For the safety analysis, i.e. the assessment of the impact of malaria treatment on hemoglobin levels or the onset of anemia, the generalized linear and latent mixed models (GLLAMM) has been implemented. We have shown how to properly apply the existing statistical tools in the analysis of these data. The prospects of this work remain in the development of guides on good practices on the methodology of the preparation and analysis and storage network for malaria data
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Lyth, Johan. "En jämförelse mellan individers självuppskattade livskvalitet och samhällets hälsopreferenser : En paneldatastudie av hjärtpatienter." Thesis, Linköpings universitet, Matematiska institutionen, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15095.

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Objective: In recent years there has been an increasing interest within the clinical (medical) science in measuring people’s health. When estimating quality of life, present practise is to use the EQ-5D questionnaire and an index which weighs the different questions. The question is what happens if the individuals estimate there own health, would it differ from the public preferences? The aim is to make a new prediction model based on the opinion of patients and compare it to the present model based on public preferences. Method: A sample of 362 patients with unstable coronary artery disease from the Frisc II trial, valued their quality of life in the acute phase and after 3, 6 and 12 months. The EQ-5D question form and also the Time Trade-off method (TTO), a direct method of valuing health was used. A regression technique managing panel data had to be used in estimating TTO by the EQ-5D and other variables like gender and age. Result: Different regression techniques vary in estimating parameters and standard errors. A Generalized Estimating Equation approach with empirical correlation structure is the most suitable regression technique for the data material. A model based on the EQ-5D question form and a continuous age variable proves to be the best model for an index derived by individuals. The difference between heart patients own opinion of health and the public preferences differs a great amount in the severe health conditions, but are rather small for healthy patients. Of the total 243 health conditions, only eight of the conditions were estimated higher by the public index. Conclusions: As the differences between the approaches are significantly large the choice of index could affect the decision making in a health economic study.
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Mayo-Bruinsma, Liesha. "Family-centered Care Delivery: Comparing Models of Primary Care Service Delivery in Ontario." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/19952.

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Family-centered care (FCC) focuses on considering the family in planning/implementing care and is associated with increased patient satisfaction. Little is known about factors that influence FCC. Using linear mixed modeling and Generalized Estimating Equations to analyze data from a cross-sectional survey of primary care practices in Ontario, this study sought to determine whether models of primary care service delivery differ in their provision of FCC and to identify characteristics of primary care practices associated with FCC. Patient-reported scores of FCC were high, but did not differ significantly among primary care models. After accounting for patient characteristics, practice characteristics were not significantly associated with patient-reported FCC. Provider-reported scores of FCC were significantly higher in Community Health Centres than in Family Health Networks. Higher numbers of nurse practitioners and clinical services on site were associated with higher FCC scores but scores decreased as the number of family physicians at a site increased.
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Santo, Jonatas Silva do Espirito. "Modelo de regressão de valor extremo para dados agrupados." Universidade Federal de São Carlos, 2013. https://repositorio.ufscar.br/handle/ufscar/4565.

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Financiadora de Estudos e Projetos
One of the distributions used to model extremal events is the type I extremevalue distribution (Gumbel distribution). The usual extreme-value regression model requires independent observations. In this work, using generalized linear model (Mc-Cullagh e Nelder, 1989) and generalized estimating equations (Liang e Zeger, 1986), we developed the extreme-value regression model when there are independent clusters formed by dependent variables. The behavior of parameter estimators of the proposed model is studied through Monte Carlo simulations.
A distribuição valor extremo tipo I, também conhecida como distribuição Gumbel, é uma das distribuições utilizadas para a modelagem de eventos extremos. Os modelos existentes de regressão valor extremo supõem que as observações sejam independentes, inviabilizando o uso desses modelos quando existe dependência entre as observações. Nesta dissertação, utilizando modelos lineares generalizados (McCullagh e Nelder, 1989) e equações de estimação generalizadas (Liang e Zeger, 1986), desenvolvemos o modelo de regress~ao valor extremo para o caso em que h a grupos independentes formados por respostas dependentes. O comportamento dos estimadoresdos parâmetros do modelo proposto é avaliada através de simulações Monte Carlo.
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Su, David, and 蘇志偉. "Applied Generalized Estimating Equations(GEE) to Financial Distress''s Forcast." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/04208829903962863846.

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Zheng, Mengjie. "Joint modeling of longitudinal and survival outcomes using generalized estimating equations." Diss., 2018. https://doi.org/10.7912/C2KS92.

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Indiana University-Purdue University Indianapolis (IUPUI)
Joint models for longitudinal and time-to-event data has been introduced to study the association between repeatedly measured exposures and the risk of an event. The use of joint models allows a survival outcome to depend on some characteristic functions from the longitudinal measures. Current estimation methods include a two-stage approach, Bayesian and maximum likelihood estimation (MLEs) methods. The twostage method is computationally straightforward but often yields biased estimates. Bayesian and MLE methods rely on the joint likelihood of longitudinal and survival outcomes and can be computationally intensive. In this work, we propose a joint generalized estimating equation framework using an inverse intensity weighting approach for parameter estimation from joint models. The proposed method can be used to longitudinal outcomes from the exponential family of distributions and is computationally e cient. The performance of the proposed method is evaluated in simulation studies. The proposed method is used in an aging cohort to determine the relationship between longitudinal biomarkers and the risk of coronary artery disease.
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"A comparison of goodness-of-fit tests for binomial generalized estimating equations (GEE) models." Tulane University, 2004.

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Binary outcomes are very common in medical and epidemiological studies. When scores are independent, logistic regression models are typically used. When outcomes are dependent, generalized estimating equations (GEE) methods are often used to analyze the correlated binary data. For any modeling procedure, an essential step is to determine goodness-of-fit (GoF) for the final model. For logistic regression, standard GoF tests have been developed and are available in most statistical software. The GoF statistics for the GEE method, however, have been developed more recently, and have not been incorporated into currently available software. Several GEE GoF statistics have been proposed (Barnhart & Williamson 1998; Horton et al. 1999; Pan 2002). The objective of this study was to compare these GEE GoF statistics using simulation data under different conditions. Sample sizes were varied, as were the possible covariates (discrete or continuous). Different models included time-dependent and time-independent covariates, quadratic components and interactions. Two or three scores per subject were generated with various correlations between scores No single GEE GoF statistic performed best under all conditions. All of them were poor at detecting the omission of the main effect for a binary time-dependent variable. Pan's statistics had the best performance in three cases: (1) detecting the omission of the interaction for binary time-dependent and time-independent covariates with two or three time-points; (2) detecting the omission of the interaction for a time-independent dichotomous variable and a time-dependent continuous variable with three time-points for exchangeable or auto-regressive correlated data; and (3) detecting the omission of a quadratic term in a time-dependent continuous variable with two time-points. Barnhart's statistics were also the most powerful statistics in the following three cases: (1) detecting the omission of the interaction for a time-independent dichotomous variable and a time-dependent continuous variable; (2) detecting the omission of the interaction for a time-independent dichotomous variable and a time-independent continuous variable; and (3) detecting the omission of the interaction for two continuous variables for two time-points. Horton's statistics had better performance in examining the omission of interaction for a time-independent dichotomous variable and a time-dependent continuous variable with three time-points independent data
acase@tulane.edu
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Sotáková, Martina. "Zobecněné odhadovací rovnice (GEE)." Master's thesis, 2020. http://www.nusl.cz/ntk/nusl-434538.

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In this thesis we are interested in generalized estimating equations (GEE). First, we introduce the term of generalized linear model, on which generalized estimating equations are based. Next we present the methos of pseudo maximum likelyhood and quasi-pseudo maximum likelyhood, from which we move on to the methods of generalized estimating equations. Finally, we perform simulation studies, which demonstrates the theoretical results presented in the thesis. 1
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Books on the topic "Generalised estimating equations (GEE)"

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Pseudo Maximum Likelihood Methode und Generalised Estimating Equations zur Analyse korrelierter Daten. Frankfurt am Main: P. Lang, 1999.

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Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects. Taylor & Francis Group, 2021.

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Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood. Taylor & Francis Group, 2006.

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Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood. Taylor & Francis Group, 2010.

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Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition. Taylor & Francis Group, 2018.

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Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition. Taylor & Francis Group, 2017.

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Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition. Taylor & Francis Group, 2018.

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Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition. Taylor & Francis Group, 2018.

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Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition. Taylor & Francis Group, 2018.

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Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood (Monographs on Statistics and Applied Probability). Chapman & Hall/CRC, 2006.

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Book chapters on the topic "Generalised estimating equations (GEE)"

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"Generalized Estimating Equations (GEE) Models." In Longitudinal Data Analysis, 131–47. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470036486.ch8.

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Jung, Sin-Ho. "Generalized Estimating Equations (GEE) Method." In Encyclopedia of Biopharmaceutical Statistics, Third Edition, 543–46. CRC Press, 2012. http://dx.doi.org/10.1201/b14674-88.

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"Marginal Models: Generalized Estimating Equations (GEE)." In Applied Longitudinal Analysis, 353–94. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119513469.ch13.

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Jung, Sin-Ho. "Generalized Estimating Equations (GEE) Method: Sample Size Estimation." In Encyclopedia of Biopharmaceutical Statistics, 543–46. Informa Healthcare, 2010. http://dx.doi.org/10.3109/9781439822463.087.

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Izquierdo, María Isabel Cifo, Verónica Alcaraz-Muñoz, and Jose Ignacio Alonso Roque. "Importance of the Physical Sports Experience in Modern Physical Education." In Advances in Early Childhood and K-12 Education, 359–76. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-9621-0.ch020.

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The main objective of this chapter was to examine whether the sporting experience determines the emotional experience of the participants when playing competitive sports games. Seventy-three students (51 boys and 22 girls) of the 2nd year of the Degree in Physical Activity and Sport Sciences of the Catholic University San Antonio of Murcia (UCAM) participated in the study. To identify the emotional intensity experienced by the participants, the Games and Emotion Scale (GES) was used, and the generalized estimating equations test (GEE) and classification trees (CHAID method) were chosen to analyze the data obtained. The results showed that participants with previous physical-sports experience experienced emotions more intensely than participants with no previous experience. The conclusion drawn was that the physical-sports experience determines the optimal emotional experience of the students.
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"Chapter 6: Longitudinal data analysis for counts and binary outcomes: generalized estimating equations (GEE)." In Analysis of Longitudinal and Cluster-Correlated Data, 96–109. Beechwood OH and Alexandria VA: Institute of Mathematical Statistics and American Statistical Association, 2004. http://dx.doi.org/10.1214/cbms/1462106082.

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Yonesaka, Suzanne M. "Asynchronous online peer judgments of intelligibility: simple task, complex factors." In CALL and complexity – short papers from EUROCALL 2019, 407–12. Research-publishing.net, 2019. http://dx.doi.org/10.14705/rpnet.2019.38.1045.

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Pronunciation learners can benefit from peer feedback in a Computer-mediated Communication (CMC) environment that allows them to notice segmentals and suprasegmentals. This paper explores the intelligibility judgments of same-L1 peers using P-Check (Version2, https://ver2.jp), a Learning Management System (LMS) plug-in that aggregates peer feedback on local intelligibility (Munro & Derwing, 2015). P-Check randomly delivers written prompts for learners to record. Recordings are randomly delivered to peers who choose from a drop-down menu which utterance was perceived. Aggregated judgments from peers and from the instructor are displayed to learners as feedback on intelligibility. This study used eight segmental contrasts: /b-v/, /s-θ/, /l-ɹ/, /l-ɹ/-clusters, /æ-ʌ/, /ɑ-ʌ/, /ɑ-oʊ/, and /i-ɪ/. Participants (N=38) made 3,451 intelligibility judgments on 1,203 recordings. The effects of rater listening discrimination proficiency and of utterance intelligibility were examined in six contrasts using Generalized Estimating Equations (GEE). Results showed that intelligibility was generally a significant predictor of judgment accuracy, but rater listening discrimination proficiency was not.
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"Generalized Estimating Equations (GEEs)." In Mixed Effects Models for Complex Data, 333–52. Chapman and Hall/CRC, 2009. http://dx.doi.org/10.1201/9781420074086-c10.

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Liu, Xian. "Generalized estimating equations (GEEs) models." In Methods and Applications of Longitudinal Data Analysis, 281–308. Elsevier, 2016. http://dx.doi.org/10.1016/b978-0-12-801342-7.00009-5.

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Conference papers on the topic "Generalised estimating equations (GEE)"

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Spinella, Toni, Sherry Stewart, Julia Naugler, Igor Yakovenko, and Sean Barrett. "The power of placebo: Does cannabidiol (CBD) expectancy alone impact acute stress and anxiety?" In 2022 Annual Scientific Meeting of the Research Society on Marijuana. Research Society on Marijuana, 2022. http://dx.doi.org/10.26828/cannabis.2022.02.000.01.

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Background. There have been notable increases in the use of cannabidiol (CBD) for therapeutic purposes, such as in the treatment of stress- and anxiety- related disorders. Preliminary research has demonstrated that CBD decreases indices of stress and anxiety. However, drug effects in humans are thought to be comprised of both pharmacological properties as well as a placebo response. Little is known about the extent to which the purported therapeutic effects of CBD result from pharmacological versus expectancy factors. Aims. The aim of this study was to evaluate whether (i) CBD expectancy alone could influence stress, anxiety, and mood, and (ii) the extent to which beliefs regarding CBD effects predicted these responses. Generalized estimating equations (GEE) were used to evaluate the research questions of interest. Methods. In this randomized crossover study, 43 health adults (23 women) attended three laboratory sessions. During the first session, they were oriented to the study and rated the extent to which they believed that CBD helped with stress, anxiety, and mood. They then participated in two identical experimental laboratory sessions, where they self-administered CBD-free hempseed oil sublingually. During one session, they were (incorrectly) informed that the oil contained CBD and in the other session, that the oil was CBD-free. Following administration, participants engaged in the Maastricht Acute Stress Test (MAST) to induce moderate levels of stress and anxiety. Heart rate variability (HRV) was assessed continuously, and subjective state (i.e., stress, anxiety, mood, other subjective states) was assessed at baseline, 90-min following oil administration, immediately following the MAST, and after a 10-min recovery period. Results. The CBD expectancy condition was associated with increased sedation as well as significant fluctuations in HRV that could indicate heightened anticipatory stress regulation. Overall, there were no observed changes in subjective stress, or anxiety, according to expectancy condition. However, participants who endorsed the strongest a priori beliefs about CBD possessing anxiolytic properties reported significantly lower anxiety in the CBD expectancy condition and higher anxiety the CBD-free expectancy condition. Conclusions. Results from this study indicated that CBD expectancy alone impacted several subjective and physiological responses. Additionally, expectancy-related factors were implicated in anxiolytic effects of CBD for those who strongly believed it was helpful for such purposes, suggesting that expectation plays some role in the purported stress- and anxiety- reducing effects of CBD. Findings from this study emphasize the need to measure and control for CBD-related expectancies in clinical research that involves the administration of CBD. Future investigations would benefit from replicating these findings and using a full balanced-placebo research design to elucidate the relative contributions of pharmacology and expectancy.
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Awalluddin, Asep S., Inge Wahyuni, and Hilda Nurmuslimah. "Analysis of Longitudinal Regression Model Using the Generalized Estimating Equation (GEE) for the Child Welfare Composite Index (CWCI) in West Java." In 1st International Conference on Mathematics and Mathematics Education (ICMMEd 2020). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/assehr.k.210508.094.

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Galski, Roberto Luiz, Heitor Patire Ju´nior, Fabiano Luis de Sousa, Jose´ Nivaldo Hinckel, Pedro Lacava, and Fernando Manuel Ramos. "GEO + ES Hybrid Optimization Algorithm Applied to the Parametric Thermal Model Estimation of a 200N Hydrazine Thruster." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47584.

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In the present paper, a hybrid version of the Generalized Extremal Optimization (GEO) and Evolution Strategies (ES) algorithms [1], developed in order to conjugate the convergence properties of GEO with the self-tuning characteristics present in the ES, is applied to the estimation of the temperature distribution of the film cooling near the internal wall of a thruster. The temperature profile is determined through an inverse problem approach using the hybrid. The profile was obtained for steady-state conditions, were the external wall temperature along the thruster is considered as a known input. The Boltzmann’s equation parameters [2], which define the cooling film temperature profile, are the design variables. Results using simulated data showed that this approach was efficient in recuperating those parameters. The approach showed here can be used on the design of thrusters with lower wall temperatures, which is a desirable feature of such devices.
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Kraev, Vyacheslav M., and Dmitry S. Yanyshev. "On the Analysis of Turbulent Transient Flows in Channels." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22291.

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The problem of designing different devices under unsteady conditions is still remaining one of the critical ones, and cannot be fully resolved yet. So analysis of unsteady thermal and hydrodynamic processes is one of the determinants in aviation, astronautics, shipbuilding, cryogenics, chemical industry, etc. By now, considerable test data had been obtained for unsteady single-phase flows in round tubes, flat ducts, and in shaped channels. It allows carrying out one-dimensional analysis in a variety of heat-stressed structures and heat exchangers. Experimental researches and theoretical estimations show that values of heat transfer and friction coefficients may be three or even four times larger than the results of quasi-steady analysis. Turbulent flow structure researches conducted in Moscow Aviation Institute (MAI) showed that unsteadiness of mass flow rate at the inlet of the channel influences greatly on the flow structure. According to this, hydrodynamic unsteadiness should considerably affect on heat transfer. This influence may be explained by flow thermal inertia, changing of the flow turbulent structure and gas radial flow-over provided by velocity profile restructuring. Basing on the experiment, one can get optimized flow acceleration law, so that pressure losses due to friction will be minimal. The experimental data was generalized into some empirical formulae for Nusselt number and friction coefficient, so that one-dimensional engineering calculations could be provided. Nevertheless, the problem of numerical analysis of flow in tubes with transient mass flow at the inlet using RANS equations is yet unresolved. Analysis performed in MAI showed that most popular and widely used k-epsilon turbulent model cannot be applied in this particular case. The results of calculations performed with this model do not match with experimental data. For example, the results of calculation performed at Moscow Power Engineering Institute are directly opposite to the experimental data, viz the flow acceleration leads to Nusselt number and friction coefficient decreasing and vice versa. Results of calculations with k-epsilon performed in MAI are also unsatisfactory and do not go with the experimental data. The equations of k-omega based models contain dynamic viscosity terms and do not need wall functions. Results of MAI calculations with Menter’s Shear Stress Transport model go with the experimental data qualitatively. The results of these calculations are stated.
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Reports on the topic "Generalised estimating equations (GEE)"

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Lubowa, Nasser, Zita Ekeocha, Stephen Robert Byrn, and Kari L. Clase. Pharmaceutical Industry in Uganda: A Review of the Common GMP Non-conformances during Regulatory Inspections. Purdue University, December 2021. http://dx.doi.org/10.5703/1288284317442.

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The prevalence of substandard medicines in Africa is high but not well documented. Low and Middle-Income Countries (LMICs) are likely to face considerable challenges with substandard medications. Africa faces inadequate drug regulatory practices, and in general, compliance with Good Manufacturing Practices (GMP) in most of the pharmaceutical industries is lacking. The majority of pharmaceutical manufacturers in developing countries are often overwhelmed by the GMP requirements and therefore are unable to operate in line with internationally acceptable standards. Non-conformances observed during regulatory inspections provide the status of the compliance to GMP requirements. The study aimed to identify the GMP non-conformances during regulatory inspections and gaps in the production of pharmaceuticals locally manufactured in Uganda by review of the available 50 GMP reports of 21 local pharmaceutical companies in Uganda from 2016. The binary logistic generalized estimating equations (GEE) model was applied to estimate the association between odds of a company failing to comply with the GMP requirements and non-conformances under each GMP inspection parameter. Analysis using dummy estimation to linear regression included determination of the relationship that existed between the selected variables (GMP inspection parameters) and the production capacity of the local pharmaceutical industry. Oral liquids, external liquid preparations, powders, creams, and ointments were the main categories of products manufactured locally. The results indicated that 86% of the non-conformances were major, 11% were minor, and 3% critical. The majority of the non-conformances were related to production (30.1%), documentation (24.5%), and quality control (17.6%). Regression results indicated that for every non-conformance under premises, equipment, and utilities, there was a 7-fold likelihood of the manufacturer failing to comply with the GMP standards (aOR=6.81, P=0.001). The results showed that major non-conformances were significantly higher in industries of small scale (B=6.77, P=0.02) and medium scale (B=8.40, P=0.04), as compared to those of large scale. This study highlights the failures in quality assurance systems and stagnated GMP improvements in these industries that need to be addressed by the manufacturers with support from the regulator. The addition of risk assessment to critical production and quality control operations and establishment of appropriate corrective and preventive actions as part of quality management systems are required to ensure that quality pharmaceuticals are manufactured locally.
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