Abstract
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 language | English |
|---|---|
| Pages (from-to) | 181-186 |
| Number of pages | 6 |
| Journal | Computer Methods and Programs in Biomedicine |
| Volume | 59 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1999 Jun 1 |
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All Science Journal Classification (ASJC) codes
- Software
- Computer Science Applications
- Health Informatics
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A comparative study for stepwise correlated binary regression. / Sohn, So Young.
In: Computer Methods and Programs in Biomedicine, Vol. 59, No. 3, 01.06.1999, p. 181-186.Research output: Contribution to journal › Article
TY - JOUR
T1 - A comparative study for stepwise correlated binary regression
AU - Sohn, So Young
PY - 1999/6/1
Y1 - 1999/6/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0345517096&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0345517096&partnerID=8YFLogxK
U2 - 10.1016/S0169-2607(99)00005-X
DO - 10.1016/S0169-2607(99)00005-X
M3 - Article
C2 - 10386767
AN - SCOPUS:0345517096
VL - 59
SP - 181
EP - 186
JO - Computer Methods and Programs in Biomedicine
JF - Computer Methods and Programs in Biomedicine
SN - 0169-2607
IS - 3
ER -