Correlated response data arise often in biomedical studies. The generalized estimation equation (GEE) approach is widely used in regression analysis for such data. However, there are few methods available to check the adequacy of regression models in GEE. In this paper, a graphical method is proposed based on Cook and Weisberg's marginal model plot. A bootstrap method is applied to obtain the r...

BACKGROUND Incarceration has been associated with a number of health-related harms among injection drug users (IDU). However, little is known about the prevalence and correlates of incarceration among community-based samples of IDU. METHODS We examined the prevalence and correlates of recent incarceration among IDU in the Scientific Evaluation of Supervised Injecting (SEOSI) cohort examined b...

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...

This paper considers inference methods for case-control logistic regression in longitudinal setups. The motivation is provided by an analysis of plains bison spatial location as a function of habitat heterogeneity. The sampling is done according to a longitudinal matched case-control design in which, at certain time points, exactly one case, the actual location of an animal, is matched to a num...

Model selection is a central component of data analysis Though there are a variety of methods for likelihood based estimation methods there are relatively few for non likelihood based generalized linear models GLM such as in the quasi likelihood and generalized es timating equation GEE approaches In this paper we develop basic and bias corrected bootstrap approaches to estimate the predictive m...

This paper discusses varied ideas on games, learning, and digital literacy for 21st-century education as theorized and practiced by the author and James Paul Gee, and their colleagues. With attention to games as means for learning, the author links Gee’s theories to the learning sciences tradition (particularly those of the MIT Constructionists) and extending game media literacy to encompass “w...

Researchers are often interested in analyzing data that arise from a longitudinal or clustered design. Although there are a variety of standard likelihood-based approaches to analysis when the outcome variables are approximately multivariate normal, models for discrete-type outcomes generally require a different approach. Liang and Zeger formalized an approach to this problem using generalized ...

Vinod (1997, 1998) discuss the Godambe-Durbin theory of estimating functions (EFs) and its potential in econometrics. Here we consider a popular application of EFs called generalized estimating equations (GEE). It is typically applied to panel data, where the heteroscedasticity is analytically related to , the regression parameter, and where the dependent variable is binary. Geddes (1997) studi...

Surveys often contain qualitative variables for which respondents may select any number of the outcome categories. For instance, for the question "What type of contraception have you used?" with possible responses (oral, condom, lubricated condom, spermicide, and diaphragm), respondents would be instructed to select as many of the outcomes that apply. This situation is known as multiple respons...

Generalized estimating equations (GEE) fit parameters based on sums of weighted residuals, which may be applied for example to the Poisson distribution. We discuss Generalized Poisson (GP) response data. This distribution has a more flexible variance function than the Poisson distribution and has an additional dispersion parameter. To fit this parameter, second level estimating equations based ...