Sensitivity analysis for generalized estimating equation with non‐ignorable missing data

Hui Gong and Kin Wai Chan

Scandinavian Journal of Statistics, 2026, vol. 53, issue 2, 735-762

Abstract: Many incomplete‐data statistical inference procedures are developed under the missing at random (MAR) assumption. However, the MAR assumption has been criticized as being overly strong for real‐data problems, and is unverifiable by using observed data. To handle data that are missing not at random (MNAR), sensitivity analysis has been proposed to investigate how conclusions are perturbed if the unverifiable MAR assumption is violated to a certain degree. This article proposes a new framework called multiple sensitivity models (MSMs) for performing general parameter estimation with the generalized estimating equation (GEE) method. Given user‐specified sensitivity parameters, a range of estimators is derived by solving the roots of the bounds of MSM‐assisted GEEs. Furthermore, we derive a representation for the proposed estimator so that it can be decomposed into several simpler estimators. It allows us to investigate the impact of different missing patterns. An asymptotically valid percentile bootstrap confidence region (CR) is also proposed. Theoretical justification is provided together with empirical evidence, which verifies the usefulness of the proposal's sensitivity analysis.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/sjos.70060

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:53:y:2026:i:2:p:735-762

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 ().