A joint model for repeated events of different types and multiple longitudinal outcomes with application to a follow-up study of patients after kidney transplant.
about
Dynamic prediction of recurrent events data by landmarking with application to a follow-up study of patients after kidney transplant.Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues.Joint analysis of longitudinal and survival AIDS data with a spatial fraction of long-term survivors: A Bayesian approach.
P2860
A joint model for repeated events of different types and multiple longitudinal outcomes with application to a follow-up study of patients after kidney transplant.
description
2014 nî lūn-bûn
@nan
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
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@zh
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@zh-cn
name
A joint model for repeated eve ...... ients after kidney transplant.
@en
type
label
A joint model for repeated eve ...... ients after kidney transplant.
@en
prefLabel
A joint model for repeated eve ...... ients after kidney transplant.
@en
P2093
P2860
P356
P1433
P1476
A joint model for repeated eve ...... ients after kidney transplant.
@en
P2093
Aeilko H Zwinderman
Jammbe Z Musoro
Ronald B Geskus
P2860
P304
P356
10.1002/BIMJ.201300167
P577
2014-10-15T00:00:00Z