Advanced Search
MyIDEAS: Login to save this article or follow this journal

Efficiency Comparisons in Multivariate Multiple Regression with Missing Outcomes

Contents:

Author Info

  • Rotnitzky, Andrea
  • Holcroft, Christina A.
  • Robins, James M.

Abstract

We consider a follow-up study in which an outcome variable is to be measured at fixed time points and covariate values are measured prior to start of follow-up. We assume that the conditional mean of the outcome given the covariates is a linear function of the covariates and is indexed by occasion-specific regression parameters. In this paper we study the asymptotic properties of several frequently used estimators of the regression parameters, namely the ordinary least squares (OLS), the generalized least squares (GLS), and the generalized estimating equation (GEE) estimators when the complete vector of outcomes is not always observed, the missing data patterns are monotone and the data are missing completely at random (MCAR) in the sense defined by Rubin [11]. We show that when the covariance of the outcome given the covariates is constant, as opposed to the nonmissing data case: (a) the GLS estimator is more efficient than the OLS estimator, (b) the GLS estimator is inefficient, and (c) the semiparametric efficient estimator in a model that imposes linear restrictions only on the conditional mean of the last occasion regression can be less efficient than the efficient estimator in a model that imposes linear restrictions on the conditional means of all the outcomes. We provide formulae and calculations of the asymptotic relative efficiencies of the considered estimators in three important cases: (1) for the estimators of the occasion-specific means, (2) for estimators of occasion-specific mean differences, and (3) for estimators of occasion-specific dose-response model parameters.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.sciencedirect.com/science/article/B6WK9-45K12X4-7/2/9b02284a00ab12b8e1286630d0831a45
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Elsevier in its journal Journal of Multivariate Analysis.

Volume (Year): 61 (1997)
Issue (Month): 1 (April)
Pages: 102-128

as in new window
Handle: RePEc:eee:jmvana:v:61:y:1997:i:1:p:102-128

Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description

Order Information:
Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
Web: https://shop.elsevier.com/order?id=622892&ref=622892_01_ooc_1&version=01

Related research

Keywords: generalized estimating equations generalized least squares missing data repeated measures semiparametric efficient;

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
Full references (including those not matched with items on IDEAS)

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:eee:jmvana:v:61:y:1997:i:1:p:102-128. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.