Results 211 to 220 of about 57,784 (254)

Generalized estimating equations

2002
Correlated datasets develop when multiple observations are collected from a sampling unit (e.g., repeated measures of a bank over time, or hormone levels in a breast cancer patient over time), or from clustered data where observations are grouped based on a shared characteristic (e.g., observations on different banks grouped by zip code, or on cancer ...
Geys, H., Molenberghs, G., Ryan, L.
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Generalized Estimating Equation

2017
The generalized estimating equation (GEE) uses a quasi-likelihood approach for analyzing data with correlated outcomes. This is an extension of GLM and uses quasi-likelihood method for cluster or repeated outcomes. If observations on outcome variable are repeated, it is likely that the observations are correlated.
M. Ataharul Islam, Rafiqul I. Chowdhury
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Generalized Estimating Equations

Journal of the American Statistical Association, 2004
(2004). Generalized Estimating Equations. Journal of the American Statistical Association: Vol. 99, No. 465, pp. 297-298.
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SAGA Application for Generalized Estimating Equations Analysis

2023
Logistic regression models seek to identify the influence of different variables/factors on a response variable of interest. These are normally used in the field of medicine as it allows verifying which factors influence the presence of certain pathologies. However, most of these models do not consider the correlation between the variables under study.
Luís Moncaixa, Ana Cristina Braga
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Performance of Generalized Estimating Equations in Practical Situations

Biometrics, 1994
Moment methods for analyzing repeated binary responses have been proposed by Liang and Zeger (1986, Biometrika 73, 13-22), and extended by Prentice (1988, Biometrics 44, 1033-1048). In their generalized estimating equations (GEE), both Liang and Zeger (1986) and Prentice (1988) estimate the parameters associated with the expected value of an individual'
Lipsitz, Stuart R., Fitzmaurice, Garrett M., Orav, Endel J., Laird, Nan M.   +3 more
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Generalized moment estimation for uncertain differential equations

Applied Mathematics and Computation, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Local Influence in Generalized Estimating Equations

Scandinavian Journal of Statistics, 2007
Abstract. We investigate the influence of subjects or observations on regression coefficients of generalized estimating equations (GEEs) using local influence. The GEE approach does not require the full multivariate distribution of the response vector. We extend the likelihood displacement to a quasi‐likelihood displacement, and propose local influence
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A Comparison of Bias-Corrected Covariance Estimators for Generalized Estimating Equations

Journal of Biopharmaceutical Statistics, 2013
Although asymptotically the sandwich covariance estimator is consistent and robust with respect to the selection of the working correlation matrix, when the sample size is small, its bias may not be negligible. This article compares the small sample corrections for the sandwich covariance estimator as well as the inferential procedures proposed by ...
Chunpeng, Fan, Donghui, Zhang, Cun-Hui, Zhang   +2 more
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Generalized moment estimation of stochastic differential equations

Computational Statistics, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Márcio Poletti Laurini, Luiz Koodi Hotta   +1 more
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A generalized estimating/pseudo-score equations approach for the estimation of structural equation models [PDF]

, 2000
The results of two simulation studies suggest a mixed `generalized estimating/pseudo-score equations' approach to lead to more efficient estimators than a GEE approach proposed by Qu, Williams, Beck and Medendorp (1992) or a three-stage approach as proposed e.g.
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