Area:
Psychometrics Psychology
We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Jack McArdle is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2011 — 2013 |
Mcardle, Jack Zhou, Yan (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Doctoral Dissertation Research: Dynamic Analyses of Cognition and Mortality in the Oldest Old @ University of Southern California
Evidence is accumulating that cognitive abilities are inversely associated with mortality, and this association seems to be present irrespective of study population, cohort, and the cognitive tests used. Cognitive abilities are not traditionally considered in epidemiology, however, and their additional value to the prediction of mortality is not clear. On the other hand, cognitive decline is viewed as one of the multifaceted aspects of the aging process, but few studies have related characteristics in the changing process of cognition to mortality. The examination of these problems largely has been impeded by methodological difficulties. This project will examine several novel methods to investigate the relations of cognition (in particular, episodic memory and verbal ability) and mortality using longitudinal data in a national sample of U.S. adults aged 70 years and older. These methods will be employed in a progressive order and will include latent curve models, mixed-effects change point models, joint growth and survival models, traditional survival analysis, and recursive partitioning techniques (survival trees and random forests).
The project will examine cognitive change in the oldest population cohort and relate it to mortality. The increasing proportion of this group in the population is impacting many social and economic issues. The substantive results from this project may be especially informative for policy makers in considering hospice care plans. Methodologically, this project will compare alternative approaches to analyzing longitudinal and survival data and will employ exploratory data mining in survival analysis. The methodological finding may have broad applications for many fields in the behavioral and health sciences. As a Doctoral Dissertation Research Improvement award, support is provided to enable a promising student to establish a strong, independent research career.
|
1 |