Goodness‐of‐fit Tests for GEE with Correlated Binary Data

Wei Pan

Scandinavian Journal of Statistics, 2002, vol. 29, issue 1, 101-110

Abstract: The marginal logistic regression, in combination with GEE, is an increasingly important method in dealing with correlated binary data. As for independent binary data, when the number of possible combinations of the covariate values in a logistic regression model is much larger than the sample size, such as when the logistic model contains at least one continuous covariate, many existing chi‐square goodness‐of‐fit tests either are not applicable or have some serious drawbacks. In this paper two residual based normal goodness‐of‐fit test statistics are proposed: the Pearson chi‐square and an unweighted sum of residual squares. Easy‐to‐calculate approximations to the mean and variance of either statistic are also given. Their performance, in terms of both size and power, was satisfactory in our simulation studies. For illustration we apply them to a real data set.

Date: 2002
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://doi.org/10.1111/1467-9469.00091

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:29:y:2002:i:1:p:101-110

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898

Access Statistics for this article

Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist

More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().