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http://scihub22266oqcxt.onion/ C5015698!5015698!27616941     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Stat+Softw 2016 ; 71 (3): ä Nephropedia Template TP {{tp|p=27616941|t=2016. JMFit: A SAS Macro for Joint Models of Longitudinal and Survival Data |pdf=|usr=}}{{27616941}} gab.com Text JMFit: A SAS Macro for Joint Models of Longitudinal and Survival Data JO: J Stat Softw http://www.kidney.de/pget.php?&tw=1&pmid=27616941 #FOAvip Joint models for longitudinal and survival data now have a long history of being used in clinical trials or other studies in which the goal is to assess a treatment effect while accounting for a longitudinal biomarker such as patient-reported outcomes or immune responses. Although software has been developed for fitting the joint model, no software packages are currently available for simultaneously fitting the joint model and assessing the fit of the longitudinal component and the survival component of the model separately as well as the contribution of the longitudinal data to the fit of the survival model. To fulfill this need, we develop a SAS macro, called JMFit. JMFit implements a variety of popular joint models and provides several model assessment measures including the decomposition of AIC and BIC as well as ?AIC and ?BIC recently developed in Zhang et al. (2014). Examples with real and simulated data are provided to illustrate the use of JMFit. Twit Text FOAVip JMFit: A SAS Macro for Joint Models of Longitudinal and Survival Data ????J Stat Softw http://www.kidney.de/pget.php?&tw=1&pmid=27616941 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27616941 #FOAvip English Wikipedia <ref>{{Cite pmid|27616941}}</ref> JMFit: A SAS Macro for Joint Models of Longitudinal and Survival Data #MMPMID27616941 Zhang D; Chen MH; Ibrahim JG; Boye ME; Shen W J Stat Softw 2016[Jul]; 71 (3): ä PMID27616941show ga Joint models for longitudinal and survival data now have a long history of being used in clinical trials or other studies in which the goal is to assess a treatment effect while accounting for a longitudinal biomarker such as patient-reported outcomes or immune responses. Although software has been developed for fitting the joint model, no software packages are currently available for simultaneously fitting the joint model and assessing the fit of the longitudinal component and the survival component of the model separately as well as the contribution of the longitudinal data to the fit of the survival model. To fulfill this need, we develop a SAS macro, called JMFit. JMFit implements a variety of popular joint models and provides several model assessment measures including the decomposition of AIC and BIC as well as ?AIC and ?BIC recently developed in Zhang et al. (2014). Examples with real and simulated data are provided to illustrate the use of JMFit. äJMFit: A SAS Macro for Joint Models of Longitudinal and Survival Data (epmc).pdf DeepDyve Pubget Overpricing