Likelihood analysis of the multivariate ordinal probit model for repeated and spatial ordered categorical responses Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/fx719p74n

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • This dissertation is about the likelihood analysis of ordered categorical responses in a longitudinal/spatial study, meaning regression-like analysis when the response variable is categorical with ordered categories, and is measured repeatedly over time or space on the experimental or sampling units. Particular attention is given to the multivariate ordinal probit regression model, in which the correlation between ordered categorical responses on the same unit at different times or locations is modeled with a latent variable that has a multivariate normal distribution. An algorithm for maximum likelihood analysis of this model is proposed and the analysis is demonstrated on several examples. Simulations show that the maximum likelihood estimates can be substantially more efficient than generalized estimating equations (GEE) estimates of regression coefficients. We also propose likelihood analysis of a regression model for spatial-temporal ordered categorical data, and with particular attention to an investigation of determinants of Coho salmon densities in Oregon. This approach avoids defining a neighborhood for each site, which is an awkward step that is required for existing approaches.
Resource Type
Date Available
Date Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Keyword
Subject
Rights Statement
Language
File Format
File Extent
  • 1006332 bytes
Replaces
Additional Information
  • description.provenance : Rejected by Julie Kurtz(julie.kurtz@oregonstate.edu), reason: Rejecting so you can convert your two PDF files to one PDF file. 1) open the item that was rejected. 2) replace the file that's attached w/revised file 3) resubmit the item. Thanks, Julie on 2007-03-14T16:05:21Z (GMT)
  • description.provenance : Submitted by Yonghai Li (liyo@onid.orst.edu) on 2007-03-15T07:04:34Z No. of bitstreams: 1 Dissertation_Yonghai_Li.pdf: 1006332 bytes, checksum: 3c6319d8967dc32a2368fd846d181e14 (MD5)
  • description.provenance : Made available in DSpace on 2007-03-28T20:41:25Z (GMT). No. of bitstreams: 1 Dissertation_Yonghai_Li.pdf: 1006332 bytes, checksum: 3c6319d8967dc32a2368fd846d181e14 (MD5)
  • description.provenance : Submitted by Yonghai Li (liyo@onid.orst.edu) on 2007-03-05T07:59:20Z No. of bitstreams: 2 text.pdf: 997935 bytes, checksum: 4a6054a8ea53f75815bc9bf0cd2d7e5f (MD5) pretext.pdf: 43347 bytes, checksum: 3c37d483ffae48e62b17e73ee4cfc8e8 (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2007-03-15T15:31:54Z (GMT) No. of bitstreams: 1 Dissertation_Yonghai_Li.pdf: 1006332 bytes, checksum: 3c6319d8967dc32a2368fd846d181e14 (MD5)

Relationships

In Administrative Set:
Last modified: 08/01/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items