This is an R29 re- application in which the investigator intends to develop statistical methods to analyze multivariate survival data. Frailty concepts will be used to model the correlated survival data. Initially, methods will be developed in a bivariate context, but most will then be extended to the multivariate situation. Four methods are proposed for estimating co- variate effects each of which is expected to perform better than existing methods in terms of efficiency. Large sample theory will be developed and small sample statistical properties will be investigated. In addition, two methods have been proposed for estimating the association between survival times. These results will be extended to investigate the use of frailty models and crossover designs involving survival data. Another important objective of this proposal is to develop statistical models which are useful in genetic epidemiology. The applicant will focus on two issues: (1) she proposes new survival models for the analysis of MZ and DZ twin data to obtain interpretable parameters representing genetic and environmental effects; (2) the applicant also proposes new multivariate survival models that can handle different correlations among family members. She will extend the methods proposed in specific aim 1 to make inference on the parameters of these models and their statistical properties will be investigated; this is specific aim 2. A data set on cardiovascular disease from NHLBI will be used to assess the appropriateness of the models. These data are on a study of twins. The methods for assessing the frailty assumption for a given data set will also be evaluated in this study. This will be accomplished by proposing diagnostic plots and goodness-of-fit test statistics, as well as studying the performance of the preceding methods when the assumptions of frailty models are violated. Three data sets will be analyzed to show the use of the proposed methods and to yield a more complete understanding of the relative merits and limitations of the use of frailty models in practical applications.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
First Independent Research Support & Transition (FIRST) Awards (R29)
Project #
5R29GM052495-02
Application #
2332005
Study Section
Special Emphasis Panel (ZRG7-STA (23))
Project Start
1996-02-01
Project End
2001-01-31
Budget Start
1997-02-01
Budget End
1998-01-31
Support Year
2
Fiscal Year
1997
Total Cost
Indirect Cost
Name
Emory University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
042250712
City
Atlanta
State
GA
Country
United States
Zip Code
30322
Viswanathan, B; Manatunga, A K (2001) Diagnostic plots for assessing the frailty distribution in multivariate survival data. Lifetime Data Anal 7:143-55
Price, D L; Manatunga, A K (2001) Modelling survival data with a cured fraction using frailty models. Stat Med 20:1515-27
Manatunga, A K; Chen, S (2000) Sample size estimation for survival outcomes in cluster-randomized studies with small cluster sizes. Biometrics 56:616-21
Manatunga, A K; Oakes, D (1999) Parametric analysis for matched pair survival data. Lifetime Data Anal 5:371-87
Chen, M H; Manatunga, A K; Williams, C J (1998) Heritability estimates from human twin data by incorporating historical prior information. Biometrics 54:1348-62
Sun, F; Ashley-Koch, A E; Durham, L K et al. (1998) Testing for contributions of mitochondrial DNA mutations to complex diseases. Genet Epidemiol 15:451-69
Williamson, J M; Manatunga, A K (1997) Assessing interrater agreement from dependent data. Biometrics 53:707-14