Search results for "longitudinal measurements"
showing 3 items of 3 documents
Bayesian subcohort selection for longitudinal covariate measurements in follow‐up studies
2022
We propose an approach for the planning of longitudinal covariate measurements in follow-up studies where covariates are time-varying. We assume that the entire cohort cannot be selected for longitudinal measurements due to financial limitations, and study how a subset of the cohort should be selected optimally, in order to obtain precise estimates of covariate effects in a survival model. In our approach, the study will be designed sequentially utilizing the data collected in previous measurements of the individuals as prior information. We propose using a Bayesian optimality criterion in the subcohort selections, which is compared with simple random sampling using simulated and real follo…
Efficient design and modeling strategies for follow-up studies with time-varying covariates
2015
Epidemiological studies can often be designed in several ways, some of which may be more optimal than others. Possible designs may differ in the required resources or the ability to provide reliable answers to the questions under study. In addition, once the data are collected, the selected modeling approach may affect how efficiently the data are utilized. The purpose of this dissertation is to investigate efficient designs and analysis meth ods in follow-up studies with longitudinal measurements. A key question is how to select optimally a subcohort for a new longitudinal covariate measurement if we cannot afford to measure the entire cohort. Another key question we consider is how to determine …
How many longitudinal covariate measurements are needed for risk prediction?
2014
Abstract Objective In epidemiologic follow-up studies, many key covariates, such as smoking, use of medication, blood pressure, and cholesterol, are time varying. Because of practical and financial limitations, time-varying covariates cannot be measured continuously, but only at certain prespecified time points. We study how the number of these longitudinal measurements can be chosen cost-efficiently by evaluating the usefulness of the measurements for risk prediction. Study Design and Setting The usefulness is addressed by measuring the improvement in model discrimination between models using different amounts of longitudinal information. We use simulated follow-up data and the data from t…