Multivariate survival data arise when each study subject may experience multiple events or when study subjects are clustered into groups. Statistical analyses of such data need to account for the intra-cluster dependence through appropriate modeling. Frailty models are the most popular for such failure time data. However, there are other approaches which model the dependence structure directly....

Recurrent events data have been increasingly important in clinical studies. There are many methods to analyze this type of data. Several papers have been presented about how to perform repeated events analysis in SAS. In clinical studies, we may encounter recurrent disease episodes in patients with a terminal event such as death, and the terminal event is often strongly correlated with the recu...

MICHAEL LINDSEY PENNELL: BAYESIAN SEMIPARAMETRIC METHODS FOR LONGITUDINAL, MULTIVARIATE, AND SURVIVAL DATA. (Under the direction of Dr. David Dunson.) In many biomedical studies, the observed data may violate the assumptions of standard parametric methods. In these situations, Bayesian methods are appealing since nonparametric priors, such as the Dirichlet process (DP), can incorporate a priori...

The shared frailty models allow for unobserved heterogeneity or for statistical dependence between observed survival data. The most commonly used estimation procedure in frailty models is the EM algorithm, but this approach yields a discrete estimator of the distribution and consequently does not allow direct estimation of the hazard function. We show how maximum penalized likelihood estimation...

b a c k g r o u n d & aim: the excess hazard rate proposed by andersen and vaeth may underestimate the long-term excess hazard rate for cancer survival. zahl explained the phenomenon by continuous selection of the most robust individuals after diagnosis. he applied correlated inverse gaussian and gamma  frailty  models  to estimate  excess  intensity  and reached  a better  estimate  of the rat...

Frailty models account for the clustering present in event time data. A proportional hazards model with shared frailties expresses the hazard for each subject. Often a one-parameter gamma distribution is assumed for the frailties. In this paper, we construct formal goodness-of-fit tests to test for gamma frailties. We construct a new class of frailty models that extend the gamma frailty model b...

seminars at Toronto University and ESSEC Business School for useful comments. We gratefully acknowledge financial support of the chair QUANTVALLEY/Risk Foundation: " Quantitative Management Initiative " and the Swiss National Science Foundation through the NCCR FINRISK network. Abstract In this paper we examine the dependence between the liquidation risks of individual hedge funds. This depende...

Family survival data can be used to estimate the degree of genetic and environmental contributions to the age at onset of a disease or of a specific event in life. The data can be modeled with a correlated frailty model in which the frailty variable accounts for the degree of kinship within the family. The heritability (degree of heredity) of the age at a specific event in life (or the onset of...

OBJECTIVE To analyze if demographic and socioeconomic factors and factors related to health and health services are associated with frailty in community-dwelling older adults. METHODS This is a cross-sectional study with 339 older adults (60 years old or more) living in Juiz de Fora, State of Minas Gerais, Brazil, in 2015. A household survey was carried out and frailty was evaluated using the...

Results: Frailty significantly correlates with all the 8 dimensions of the HR-QOL even after controlling for covariates. Also frailty status significantly correlates with age, education, Body Mass Index (BMI), function, depression and cognition. By linear Correlation coefficient a significant correlation between frailty and HR-QOL, age, function, cognition and depression was found. Conclusion: ...