A comparative study for stepwise correlated binary regression

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2 Citations (Scopus)


Real-time monitored binary data are often recorded along with a large amount of associated covariates for biomedical image processing. Serially measured binary outcomes and covariates could be autocorrelated. Appropriate variable selection schemes are necessary to find a set of influential covariates on the changes in the correlated binary outcomes. Selected variables can be used as feedback information to reduce the dimension of the database. In this context, we examine the performance of the stepwise correlated binary regression. Several realistic situations of the real-time monitored binary data are considered in Monte-Carlo simulation. Results of a simulation study are discussed.

Original languageEnglish
Pages (from-to)181-186
Number of pages6
JournalComputer Methods and Programs in Biomedicine
Issue number3
Publication statusPublished - 1999 Jun

Bibliographical note

Funding Information:
This work was supported by the Yonsei University Research Fund of 1997.

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Health Informatics


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