Description Details Author(s) References Examples

A joint regression model for mixed correlated binary and continuous responses is presented. In this model binary response can be dependent on the continuous response. With this model, the dependence between responses can be taken into account by the correlation between errors in the models for binary and continuous responses.

Package: | JointRegBC |

Type: | Package |

Version: | 1.0 |

Date: | 2013-05-31 |

License: | GPL (>=2) |

Ehsan Bahrami Samani and Zhale Tahmasebinejad

Maintainer: Bahrami Samani <ehsan_bahrami_samani@yahoo.com>

Bahrami Samani, E. and Tahmasebinejad. Zh.(2011). Joint Modelling of Mixed Correlated Nominal, Ordinal and Continuous Responses. Journal of Statistical Research. 45(1):37-47.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
data("Bahrami1")
gender<-Bahrami1$ GENDER
age<-Bahrami1$AGE
duration <-Bahrami1$ DURATION
y<-Bahrami1$ STEATOS
z<-Bahrami1$ BMI
sbp<-Bahrami1$ SBP
X=cbind(gender,age,duration ,sbp)
P<-lm(z~X)[[1]]
names(P)<-paste("Con_",names(P),sep="")
Q<-clogit(y~X)[[1]]
names(Q)<-paste("Binary",names(Q),sep="")
W=c(cor(y,z),var(z))
names(W)=c("Corr","Variance of Continuous Response")
ini=c(P,Q,W)
p=5;
q=4;
JointRegBC(ini,X=X,y=y,z=z,p=p,q=q)
``` |

JointRegBC documentation built on May 29, 2017, 12:14 p.m.

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