Solving Generalised Estimating Equations With Missing Data Using Pseudo Maximum Likelihood Estimation Is Equivalent to Complete Case Analysis
نویسندگان
چکیده
Arminger and Sobel proposed an approach to estimate mean and covariance structures in the presence of missing data These authors claimed that their method based on Pseudo Maximum Likelihood PML estimation may be applied if the data are missing at random MAR in the sense of Little and Rubin Rotnitzky and Robins however stated that the PML approach may yield inconsistent estimates if the data are MAR We show that the adoption of the PML approach for mean and covariance structures to mean structures in the presence of missing data as proposed by Ziegler is identical to the complete case CC estimator Nevertheless the PML approach has the computational advantage in that the association structure remains the same
منابع مشابه
Estimation of Parameters for an Extended Generalized Half Logistic Distribution Based on Complete and Censored Data
This paper considers an Extended Generalized Half Logistic distribution. We derive some properties of this distribution and then we discuss estimation of the distribution parameters by the methods of moments, maximum likelihood and the new method of minimum spacing distance estimator based on complete data. Also, maximum likelihood equations for estimating the parameters based on Type-I and Typ...
متن کاملمقایسه روش بیزی (Bayesian) و کلاسیک در برآرد پارامترهای مدل رگرسیون لجستیک با وجود مقادیر گمشده در متغیرهای کمکی
Background and Aim: Logistic regression is an analytic tool widely used in medical and epidemiologic research. In many studies, we face data sets in which some of the data are not recorded. A simple way to deal with such "missing data" is to simply ignore the subjects with missing observations, and perform the analysis on cases for which complete data are available. Materials and Methods: We c...
متن کاملEstimation in Simple Step-Stress Model for the Marshall-Olkin Generalized Exponential Distribution under Type-I Censoring
This paper considers the simple step-stress model from the Marshall-Olkin generalized exponential distribution when there is time constraint on the duration of the experiment. The maximum likelihood equations for estimating the parameters assuming a cumulative exposure model with lifetimes as the distributed Marshall Olkin generalized exponential are derived. The likelihood equations do not lea...
متن کاملتحلیل درستنمایی ماکزیمم مدل رگرسیون لجستیک در حالتی که داده های متغیرهای پیشگو کامل نیستند ولی متغیرهای کمکی وجود دارند
Background and Objectives: Missing data exist in many studies, e.g. in regression models, and they decrease the model's efficacy. Many methods have been suggested for handling incomplete data: they have generally focused on missing outcome values. But covariate values can also be missing.Materials and Methods: In this paper we study the missing imputation by the EM algorithm and auxiliary varia...
متن کاملA mixed approach and a distribution-free multiple imputation technique for the estimation of a multivariate probit model with missing values.
In the present paper a mixed generalized estimating/pseudo-score equations (GEPSE) approach together with a distribution-free multiple imputation technique is proposed for the estimation of regression and correlation structure parameters of multivariate probit models with missing values for an ordered categorical time-invariant variable. Furthermore, a generalization of the squared trace correl...
متن کامل