Some GEE advances are then introduced, consisting of Prentice's GEE approach, Zhao and Prentice's GEE method (GEE2), and the GEE models on odds ratios. Next, I compare the conditional and the marginal regression models with the argument that the application of GLMMs is a more suitable ...
Fitzmaurice GM, Laird NM, Ware JH. Marginal models: generalized estimating equa- tions. Applied Longitudinal Analysis. 2nd ed. John Wiley & Sons; 2011;353-394.Marginal Models: Generalized Estimating Equations - Fitzmaurice, Laird, et al. - 2004...
generalized estimating equations 广义估计方程 例句The longitudinal association between migraine and cognitive changes was assessed by generalized estimating equations. 在偏头痛和非偏头痛患者之间的纵向关联由普通估计方程来评估.Objective:Based on the longitudinal data,to probe how to model the generalized estima...
一、使用狀況: 廣義估計式(generalized estimating equations, GEE)是由陽明大學校長梁賡義 教授與Scott L. Zeger教授於1986年提出,並於Biometrika及Biometrics陸續發表理論與應用文章,屬於估計方法而非模式方法,用於評估迴歸係數跟標準誤(Standard error)。一般來說,GEE迴歸係數值會跟廣義線性模型(Generalized linear mo...
KEY WORDS: Computer software for statistical analysis; Generalized estimating equations; Missing data. 1. INTRODUCTION Generalized linear models (GLMs) (McCullagh and Nelder 1989) are a standard method used to fit regression models for univariate data that are presumed to follow an exponential family...
网络释义 1. 广义估计方程 1.3广义估计方程(generalized estimating equations)15-23 1.3.1 广义估计方程的基本理论16-19 1.3.2.二分类重复测量资料广义 … cdmd.cnki.com.cn|基于9个网页 2. 广义估计方程式 另以广义估计方程式(Generalized Estimating Equations)测试股权结构相关假说,以解决丛聚样本(clustered samp...
【Estimating Equations】 现在又回到exponential family,尝试对感兴趣的参数进行估测。 假设,(Y_1,\mathbf X_1),...,(Y_n,\mathbf X_n) 是相互独立的,并且服从exponential family里面对分布 Y_i\sim f(y_i|\theta_i) ,用canonical density和natural parameter \theta 表述为 f(y_i;\theta_i)=exp\...
Marginal models: Generalized estimating equations (GEE) Models for the analysis of longitudinal data must recognize the relationship between serial observations on the same unit. Multivariate models with general... GM Fitzmaurice,NM Laird,JH Ware 被引量: 13发表: 2004年 Comparison of generalized estima...
. glm union age not_smsa, family(gauss) link(identity)Iteration 0: Log likelihood = -10713.086 Generalized linear models Number of obs = 19,226 Optimization : ML Residual df = 19,223 Scale parameter = .1784791 Deviance = 3430.904127 (1/df) Deviance = .1784791 Pearson = 3430.904127 (1/df...
Chapter 3 describes various types of generalized estimating equations models. Attention is devoted to population-average models and subject-specific models and their various modifications. Chapter 4 deals with residual analysis, dagnostics and testing with particular attention to goodness of fit tests. ...