Results 1 to 10 of about 47,969 (301)

Robust estimation of generalized estimating equations with finite mixture correlation matrices and missing covariates at random for longitudinal data

, 2019
Niansheng Tang, Wenjun Wang
openalex   +1 more source

An estimate for the fundamental solutions of a generalized Pell equation

Mathematische Annalen, 1956
openaire   +2 more sources

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 ...
Joseph Hilbe, James W. Hardin
openaire   +5 more sources

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.
Rafiqul I. Chowdhury, M. Ataharul Islam
openaire   +2 more sources

Diagnostic techniques in generalized estimating equations

Journal of Statistical Computation and Simulation, 2007
We consider herein diagnostic methods for the quasi-likelihood regression models developed by Zeger and Liang [Zeger, S. L., Liang, K.-Y., 1986, Longitudinal data analysis for discrete and conti-nuous outcomes. Biometrics, 42, 121–130.] to analyse discrete and continuous longitudinal data. Our proposal generalises well-known measures (projection matrix,
Maria Kelly Venezuela, Denise Aparecida Botter, Mônica Carneiro Sandoval   +2 more
openaire   +2 more sources

Generalized Estimating Equations [PDF]

, 2011
Longitudinal data occurs frequently in medical studies, particularly in clinical trials. Often, the response variable is nonnormal, for example, it may be a binary variable, that is, “improved” or “not improved”. The approach to the analysis of such data discussed in this entry is the use of generalized estimating equations, which, while making weaker ...
openaire   +2 more sources

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.
openaire   +2 more sources

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
openaire   +2 more sources

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'
Stuart R. Lipsitz, Endel J. Orav, Garrett M. Fitzmaurice, Nan M. Laird   +3 more
openaire   +3 more sources

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
openaire   +2 more sources