# Root-n estimability of some missing data models

*Ao Yuan*,
*Jinfeng Xu* and
*Gang Zheng*

*Journal of Multivariate Analysis*, 2012, vol. 106, issue C, pages 147-166

**Abstract:**
It is known that in many missing data models, for example, survival data models, some parameters are root-n estimable while the others are not. When they are, their limiting distributions are often Gaussian and easy to use. When they are not, their limiting distributions, if exists, are often non-Gaussian and difficult to evaluate. Thus it is important to have some preliminary assessments of the root-n estimability in these models. In this article, we study this problem for four missing data models: two-point interval censoring, double censoring, interval truncation, and a case-control genetic association model. For the first three models, we identify some parameters which are not root-n estimable. For some root-n estimable parameters, we derive the corresponding information bounds when they exist. Also, as the Cox regression model is commonly used for such data, we give asymptotic efficient information for these regression parameters. For the case-control genetic association model, we compute the asymptotic efficient information and relative efficiency, in relation to that of the full data, when only the case-control status data are available, as is often the case in practice.

**Keywords:** Information operator; Missing data model; Root-n estimability; Score operator (search for similar items in EconPapers)

**Date:** 2012

**References:** View references in EconPapers View complete reference list from CitEc

**Citations** Track citations by RSS feed

**Downloads:** (external link)

http://www.sciencedirect.com/science/article/pii/S0047259X11002120

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:** http://EconPapers.repec.org/RePEc:eee:jmvana:v:106:y:2012:i:c:p:147-166

**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

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

Series data maintained by Dana Niculescu ().