FMCCSD-package: Efficient Estimation of Clustered Current Status Data
In FMCCSD: Efficient Estimation of Clustered Current Status Data
Description
Current status data abounds
in the field of epidemiology and public health, where the only observable data for a subject is
the random inspection time and the event status at inspection. Motivated by such a current status
data from a periodontal study where data are inherently clustered,
we propose a unified methodology to analyze such complex data.
Author(s)
Tong Wang [aut, cre],
Kejun He [aut],
Wei Ma [aut],
Dipankar Bandyopadhyay [aut],
Samiran Sinha [aut]
Maintainer:Tong Wang <tong@stat.tamu.edu>
FMCCSD documentation built on April 14, 2020, 5:16 p.m.
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Description
Current status data abounds in the field of epidemiology and public health, where the only observable data for a subject is the random inspection time and the event status at inspection. Motivated by such a current status data from a periodontal study where data are inherently clustered, we propose a unified methodology to analyze such complex data.
Author(s)
Tong Wang [aut, cre], Kejun He [aut], Wei Ma [aut], Dipankar Bandyopadhyay [aut], Samiran Sinha [aut]
Maintainer:Tong Wang <tong@stat.tamu.edu>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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