Quasi-likelihood for median regression models

Published

Journal Article

This article proposes quasi-likelihood equations for median regression models. The quasi-likelihood can be used for dependent observations such as repeated measurements or time series data. To construct a quasi-likelihood equation, we need to specify the relation between the median and the dispersion and also specify the dependency of the observations. If a monotone transformation of the original observation has a Laplace distribution, then the quasi-likelihood is the exact likelihood. Under moderate assumptions, the quasi-likelihood estimates are consistent and have asymptotically normal distributions. The estimates are also shown to have minimal asymptotic variance within a certain class of consistent estimates. The proposed method is illustrated using data from a clinical trial. Copyright 1996 Taylor & Francis Group, LLC.

Full Text

Duke Authors

Cited Authors

  • Jung, SH

Published Date

  • March 1, 1996

Published In

Volume / Issue

  • 91 / 433

Start / End Page

  • 251 - 257

Electronic International Standard Serial Number (EISSN)

  • 1537-274X

International Standard Serial Number (ISSN)

  • 0162-1459

Digital Object Identifier (DOI)

  • 10.1080/01621459.1996.10476683

Citation Source

  • Scopus