Identification problem of transition models for repeated measurement data with nonignorable missing values

Kosuke Morikawa and Yutaka Kano

Journal of Multivariate Analysis, 2018, vol. 165, issue C, 216-230

Abstract: In this paper, we consider a transition model on a response variable to describe repeated measurement data and we provide sufficient conditions to check model identifiability when analyzing data with nonignorable missing values. The sufficient conditions can give us intuitive model characteristics to achieve identifiability. In addition to the model assumptions on the response variable, a parametric model of the missing-data mechanism is often assumed. In this article, we consider identifiability in two situations: (i) both the response variable distribution and the missing-data mechanism are parametric; (ii) one of them is nonparametric, i.e., the global model is semiparametric. Useful identifiable models are proposed on the basis of these conditions. We also present an application to data of a comparative trial of two dosages of depot medroxyprogesterone acetate.

Keywords: Drop-out; Identifiability; Incomplete data; Not missing at random; Repeated measurement data; Transition model (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X17301318
Full text for ScienceDirect subscribers only

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:eee:jmvana:v:165:y:2018:i:c:p:216-230

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.jmva.2017.12.007

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().