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A model for multivariate binary data with covariates based on compatible conditionally specified logistic regressions Liu, Ying
Abstract
Rather than construction of a multivariate distribution from given univariate or bivariate margins, recently several papers seek to promote the development and usage of a simple but relatively unknown approach to the specification of models for dependent binary outcomes through conditional probabilities, each of which is assumed to be logistic. These recent proposals were all offered as heuristic approaches to specifying a multivariate distribution capable of representing the dependence of binary outcomes. However, they are limited in scope, for they all describe some special patterns of dependence. This thesis is concerned with a model for a multivariate binary response with covariates based on compatible conditionally specified logistic regressions. With this model, we allow for a general dependence structure for the binary outcomes. Three likelihood-based computing methods are introduced to estimate the parameters in our model. An example on the coronary bypass surgery is presented for illustration.
Item Metadata
Title |
A model for multivariate binary data with covariates based on compatible conditionally specified logistic regressions
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
1994
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Description |
Rather than construction of a multivariate distribution from given univariate or bivariate
margins, recently several papers seek to promote the development and usage of a
simple but relatively unknown approach to the specification of models for dependent
binary outcomes through conditional probabilities, each of which is assumed to be logistic.
These recent proposals were all offered as heuristic approaches to specifying a
multivariate distribution capable of representing the dependence of binary outcomes.
However, they are limited in scope, for they all describe some special patterns of dependence.
This thesis is concerned with a model for a multivariate binary response with
covariates based on compatible conditionally specified logistic regressions. With this
model, we allow for a general dependence structure for the binary outcomes.
Three likelihood-based computing methods are introduced to estimate the parameters
in our model. An example on the coronary bypass surgery is presented for illustration.
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Extent |
2135026 bytes
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Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2009-03-03
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0087512
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
1994-11
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.