PRM132 - MODELING MULTIPLE CARDIOVASCULAR EVENT HISTORY USING NESTED PARTITIONED SURVIVAL MODELS
نویسندگان
چکیده
منابع مشابه
SUGI 28: Survival Analysis Using Cox Proportional Hazards Modeling for Single and Multiple Event Time Data
Survival analysis techniques are often used in clinical and epidemiologic research to model time until event data. Using SAS® system's PROC PHREG, Cox regression can be employed to model time until event while simultaneously adjusting for influential covariates and accounting for problems such as attrition, delayed entry, and temporal biases. Furthermore, by extending the techniques for single ...
متن کاملEvent history graphs for censored survival data.
A compact graphical device for combining survival and time-varying covariate information is proposed. The proposed graph contains the Kaplan-Meier estimator for right-censored data and a simultaneous display of the behaviour of time-dependent covariate(s) and the lifetime for each subject in the sample. The observed levels of time-dependent covariates are possibly subjected to an initial dimens...
متن کاملEfficient Value Iteration Using Partitioned Models
In order to solve large-scale value iteration problems, more intelligent allocation of computing time is needed. We introduce the idea of an information frontier, which allows us to identify maximally productive regions of the problem space. We present a potential information flow metric which allows us to quantify the frontier precisely. We also introduce a partitioning scheme, which effective...
متن کاملEvent History Models for Life Course Analysis
The questions posed by life course researchers often differ in fundamental ways from those posed by sociologists, developmental psychologists, or economists (Elder, 1998; Mayer & Tuma, 1990). For example, life course researchers often focus analytic attention on transitions marking adolescence or early adulthood and the roles and statuses accompanying such transitions (Hogan & Astone, 1986; Mod...
متن کاملComplications in Event History I: Frailty Models
Basic Problem: Heterogeneity What is it? Usually thought of as unmeasured risk factors. Can be induced when a relevant covariate is not included in the model’s specification. Maybe these factors are not measured (unmeasureable?) or are unknown to exist. Heterogeneity can lead to trouble insofar as parameter estimates can be inconsistent, standard errors can be wrong, and estimates of duration d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Value in Health
سال: 2018
ISSN: 1098-3015
DOI: 10.1016/j.jval.2018.09.2252