Grant: Discovery Grants Program - Individual
University of Western Ontario
$42,000.00
Semiparametric mixture methods for the analysis of correlated counting and survival processes with applications to study design
EF 2013-14
Résumé
This proposal develops efficient methods for the design of clinical studies that monitor recurrent events, for example, skin or other cancer recurrences or epileptic seizures. Sometimes continuous monitoring of individuals experiencing recurrent events is not possible or imperative. There may be situations where, ethically, patients need not be subjected to such monitoring based on the need for care, and at the same time, funds spent in continuous or overly-frequent monitoring could be better allocated; alternatively, events may occur too frequently for their exact times of occurrence to be recorded. Statistical challenges to the design of studies that monitor recurrent events lie in determining optimal times for followup and the number of followup times required, accounting for the numerous distinctions that characterize studies of human subjects, for example, substantial heterogeneity in responses to treatments amongst individuals and missingness of data. The methods employed by the proposed research afford minimal assumptions on the underlying process that generates recurrences, making them highly generalizable.The proposal also considers methods for mapping disease or mortality rates. Maps such as these are important for epidemiological research, to suggest factors which may be linked to mortality, and in health policy, where they provide an overall description of mortality and are used to allocate health funding. The strength of the methods developed is their capacity to take into account the spatial arrangement of the regions and any correlations which exist because of such configurations. They isolate time trends that manifest at the broad regional level as well as the small-area level, thus permitting an overall provincial and localized policy impact.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
46119-2009
Name nom
Dean, Charmaine
Department département
Statistics and Actuarial Science
Organization id
36
Institution établissement
University of Western Ontario
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2013
Competition year année de concours
2009
Award amount
42000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
14
Committee name en
Statistical Sciences
Committee name fr
Statistique
Area of application code
1211
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Medical and health sciences
Area of application fr
Sciences médicales et de la santé
Research subject code
3005
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Biostatistics
Research subject fr
Biostatistiques
Partie
5
Nb partie
5
Application title
Semiparametric mixture methods for the analysis of correlated counting and survival processes with applications to study design
Keyword
NSERC
Application summary
This proposal develops efficient methods for the design of clinical studies that monitor recurrent events, for example, skin or other cancer recurrences or epileptic seizures. Sometimes continuous monitoring of individuals experiencing recurrent events is not possible or imperative. There may be situations where, ethically, patients need not be subjected to such monitoring based on the need for care, and at the same time, funds spent in continuous or overly-frequent monitoring could be better allocated; alternatively, events may occur too frequently for their exact times of occurrence to be recorded. Statistical challenges to the design of studies that monitor recurrent events lie in determining optimal times for followup and the number of followup times required, accounting for the numerous distinctions that characterize studies of human subjects, for example, substantial heterogeneity in responses to treatments amongst individuals and missingness of data. The methods employed by the proposed research afford minimal assumptions on the underlying process that generates recurrences, making them highly generalizable.The proposal also considers methods for mapping disease or mortality rates. Maps such as these are important for epidemiological research, to suggest factors which may be linked to mortality, and in health policy, where they provide an overall description of mortality and are used to allocate health funding. The strength of the methods developed is their capacity to take into account the spatial arrangement of the regions and any correlations which exist because of such configurations. They isolate time trends that manifest at the broad regional level as well as the small-area level, thus permitting an overall provincial and localized policy impact.