alexa Consistent Estimation in Generalized Linear Mixed Models with Measurement Error | OMICS International | Abstract
ISSN: 2155-6180

Journal of Biometrics & Biostatistics
Open Access

Like us on:

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Consistent Estimation in Generalized Linear Mixed Models with Measurement Error

He Li and Liqun Wang*

Department of Statistics, University of Manitoba, Canada

*Corresponding Author:
Liqun Wang
Department of Statistics
University of Manitoba, Winnipeg, Manitoba
Canada R3T 2N2
Tel: (204) 474-6270
Fax: (204) 474-7621
E-mail: [email protected]

Received date: March 20, 2012; Accepted date: April 12, 2012; Published date: April 13, 2012

Citation: Li H, Wang L (2012) Consistent Estimation in Generalized Linear Mixed Models with Measurement Error. J Biomet Biostat S7:007.doi: 10.4172/2155-6180.S7-007

Copyright: © 2012 Li H, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

We propose the instrumental variable method for consistent estimation of generalized linear mixed models with measurement error. This method does not require parametric assumptions for the distributions of the unobserved covariates or of the measurement errors, and it allows random effects to have any parametric distributions (not necessarily normal). We also propose simulation-based estimators for the situation where the marginal moments do not have closed forms. The proposed estimators are not only computationally attractive but also strongly root-n consistent. Moreover, the proposed estimators have a bounded influence function so they are robust against data outliers. The methodology is illustrated through simulation studies.

Keywords

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri & Aquaculture Journals

Dr. Krish

[email protected]

+1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

 
© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
Leave Your Message 24x7