02912oam 2200625I 450 991081491680332120230802004316.00-429-09433-71-280-12190-497866135257651-4398-3543-810.1201/b11311 (CKB)2550000000079048(EBL)830223(OCoLC)773034860(SSID)ssj0000580660(PQKBManifestationID)11385063(PQKBTitleCode)TC0000580660(PQKBWorkID)10606643(PQKB)10310743(MiAaPQ)EBC830223(Au-PeEL)EBL830223(CaPaEBR)ebr10522550(CaONFJC)MIL352576(EXLCZ)99255000000007904820180331d2012 uy 0engur|n|---|||||txtccrDynamic prediction in clinical survival analysis /Hans van Houwelingen, Hein PutterBoca Raton :CRC Press,2012.1 online resource (250 p.)Monographs on statistics and applied probability ;123"A Chapman & Hall book."1-4398-3533-0 Includes bibliographical references.The special nature of survival data -- Cox regression model -- Measuring the predictive value of a Cox model -- Calibration and revision of Cox models -- Mechanisms explaining violation of the Cox model -- Non-proportional hazards models -- Dealing with non-proportional hazards -- Dynamic predictions using biomarkers -- Dynamic prediction in multi-state models -- Dynamic prediction in chronic disease -- Penalized Cox models -- Dynamic prediction based on genomic data.In the last twenty years, dynamic prediction models have been extensively used to monitor patient prognosis in survival analysis. Written by one of the pioneers in the area, this book synthesizes these developments in a unified framework. It covers a range of models, including prognostic and dynamic prediction of survival using genomic data and time-dependent information. The text includes numerous examples using real data that is taken from the authors collaborative research. R programs are provided for implementing the methods--Provided by publisher.Monographs on statistics and applied probability ;123.Proportional hazards modelsSurvival analysis (Biometry)Proportional hazards models.Survival analysis (Biometry)615.580724Houwelingen J. C. van.1617427Putter Hein1617428MiAaPQMiAaPQMiAaPQBOOK9910814916803321Dynamic prediction in clinical survival analysis3948594UNINA