in this paper, the use of weighted pairwise likelihood instead of the full likelihood in estimating the parameters of the multivariate ar(1) is investigated. a closed formula for typical elements of the godambe information(sandwich information) is presented. some efficiency calculations are also given to discuss the feasibility andcomputational advantages of the weighted pairwise likelihood app...

A class of generalized linear mixed effects models is considered. Even though these models involve latent variables it is easy to approximate key aspects of the marginal distribution of the response given explanatory variables. Inference is based on a likelihood criterion which is implemented using a newly developed iteratively reweighted fitting algorithm. The algorithm is based on a normal ap...

we discuss in this paper the strong convergence for weighted sums of negatively orthant dependent (nod) random variables by generalized gaussian techniques. as a corollary, a cesaro law of large numbers of i.i.d. random variables is extended in nod setting by generalized gaussian techniques.

OBJECTIVES The present study aimed to investigate the trends in changes in pulmonary function and the risk factors for pulmonary function deterioration in patients with pulmonary tuberculosis after completing treatment. INTRODUCTION Patients usually have pulmonary function abnormalities after completing treatment for pulmonary tuberculosis. The time course for changes in pulmonary function an...

Epidemiologic data are often clustered within multiple levels that may not be nested within each other. Generalized estimating equations are commonly used to adjust for correlation among observations within clusters when fitting regression models; however, standard software does not currently accommodate nonnested clusters. This paper introduces a simple generalized estimating equation strategy...

Epidemiologic data are often clustered within multiple levels that may not be nested within each other. Generalized estimating equations are commonly used to adjust for correlation among observations within clusters when fitting regression models; however, standard software does not currently accommodate nonnested clusters. This paper introduces a simple generalized estimating equation strategy...

BACKGROUND Investigators designing clinical trials often use composite outcomes to overcome many statistical issues. Trialists want to maximize power to show a statistically significant treatment effect and avoid inflation of Type I error rate due to evaluation of multiple individual clinical outcomes. However, if the treatment effect is not similar among the components of this composite outcom...

Many of the classical estimation methods of statistics lead to estirnators that solve an equation. In common special cases, estimating equationbased estimators have appeal because they correspond to the maximum or minimum of an objective function. In such cases, an intuitively reasonable criterion for estimation, such as minimizing the Euclidean distance between the observation vector and the f...