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[P1–559]: A COMPARISON BETWEEN MIXED EFFECT AND JOINT MODELS FOR SURVIVAL AND LONGITUDINAL MODEL ESTIMATES
Author(s) -
Tripodis Yorghos,
DavisPlourde Kendra
Publication year - 2017
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2017.06.575
Subject(s) - joint (building) , longitudinal study , mixed model , longitudinal data , proportional hazards model , statistics , hazard , mean squared error , estimation , computer science , econometrics , mathematics , engineering , data mining , architectural engineering , chemistry , organic chemistry , systems engineering
Background: Mixed effects analysis has allowed investigators to incorporate more information by including repeated measures. Recently, joint models consisting of a cox proportional hazards model and a longitudinal mixed effects model have allowed investigators to also incorporate time-to-event data. By incorporating more information, we expect the estimates of the longitudinal portion of the joint model to be less biased and more precise. Research has shown improvement in estimation of the hazard function using joint models, but not much research has been done to investigate the differences in estimation of the longitudinal model. Methods:We investigate the effect of joint survival and longitudinal models on the precision and accuracy of the longitudinal estimates. In this study, we compared the longitudinal model with the longitudinal portion of the joint model in terms of coverage, bias, and precision using the same simulation structure used previously. Results: Our results showed that the estimate of the longitudinal portion of the joint model was more precise by 1%, but had a higher root mean square error by 7% andwas more susceptible to bias and type I error compared to the longitudinal model alone. Conclusions: Joint modeling of longitudinal and survival data offer some minor advantages with respect to precision that come at the cost of higher variability.