background to date, no study has addressed the association between race/ethnicity and obesity considering other sociodemographic and lifestyle factors in iran. objectives the current study aimed to study lifestyle and the environmental factors affecting obesity in the iranian subjects of the steps survey, 2011. patients and methods the study was conducted on 8639 subjects (aged ≥ 20 years) in t...

Quadratic inference functions (QIF) methodology is an important alternative to the generalized estimating equations (GEE) method in the longitudinal marginal model, as it offers higher estimation efficiency than the GEE when correlation structure is misspecified. The focus of this paper is on sample size determination and power calculation for QIF based on the Wald test in a marginal logistic m...

We develop a new approach to using estimating equations to estimate marginal regression models for longitudinal data with time-dependent covariates. Our approach classifies time-dependent covariates into three types – Types I, II and III. The type of covariate determines what estimating equations can be used involving the covariate. We use the generalised method of moments to make optimal use o...

Clustered data arise in many settings, particularly within the social and biomedical sciences. As an example, multiple-source reports are commonly collected in child and adolescent psychiatric epidemiologic studies where researchers use various informants (e.g. parent and adolescent) to provide a holistic view of a subject's symptomatology. Fitzmaurice et al. (1995) have described estimation of...

We consider the problem of calculating power and sample size for tests based on generalized estimating equations (GEE), that arise in studies involving clustered or correlated data (e.g., longitudinal studies and sibling studies). Previous approaches approximate the power of such tests using the asymptotic behavior of the test statistics under fixed alternatives. We develop a more accurate appr...

In this paper it is shown that the use of non singular block invariant ma trices of covariates leads to generalized estimating equations estimators GEE estimators Liang K Y Zeger S Biometrika which are identical regardless of the working correlation matrix used Moreover they are e cient McCullagh P The Annals of Statistics If on the other hand only time invariant covari ates are used the e cien...

Modelling repeated ordinal score data is a common statistical problem, across many application areas. The proportional-odds model is widely applied to such repeated ordinal scores and can be fitted in the repolr package (repeated measures proportional odds logistic regression) in R using the method of generalized estimating equations (GEE). The GEE approach specifies a model for the mean of the...

Semi-parametric approaches based on generalized estimating equations (GEE) are widely used to analyze correlated outcomes in longitudinal settings. In this paper, we present a package CRTgeeDR developed for cluster randomized trials with missing data (CRTs). For use of inverse probability weighting to adjust for missing data in cluster randomized trials, we show that other software lead to bias...

The Generalized Estimating Equations (GEE) is an approach to analyze correlated data. It is applied here to data from an epidemiological study of oesophageal cancer in a high incidence area in China to investigate familial aggregation. Regression diagnostics for mean structures and association structures are used to identify families that influence estimates of these structures. It is shown tha...

BACKGROUND The celebrated generalized estimating equations (GEE) approach is often used in longitudinal data analysis While this method behaves robustly against misspecification of the working correlation structure, it has some limitations on efficacy of estimators, goodness-of-fit tests and model selection criteria The quadratic inference functions (QIF) is a new statistical methodology that o...