Time-varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference. Estes, J. P., Nguyen, D. V., Dalrymple, L. S., Mu, Y., & Şentürk, D. Stat Med, 35(11):1834–1847, May, 2016.
Time-varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference [link]Paper  bibtex   
@article{est16tim,
    author = {Estes, Jason P. and Nguyen, Danh V. and Dalrymple, Lorien S. and Mu, Yi and \c{S}ent\"{u}rk, Damla},
    citeulike-article-id = {14240457},
    citeulike-linkout-0 = {http://dx.doi.org/10.1002/sim.6836},
    day = {20},
    
    issn = {02776715},
    journal = {Stat Med},
    keywords = {handling-deaths-when-studying-nonfatal-endpoints, multiple-endpoints, survival-analysis, truncation-by-death},
    month = may,
    number = {11},
    pages = {1834--1847},
    posted-at = {2016-12-29 15:52:57},
    priority = {2},
    title = {{Time-varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference}},
    url = {http://dx.doi.org/10.1002/sim.6836},
    volume = {35},
    year = {2016}
}

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