Grant: Discovery Grants Program - Individual
Memorial University of Newfoundland
$10,703.00
Simultaneous statistical inference under order restrictions and its application to dose-response studies
EF 2006-07
Résumé
SUMMARY OF PROPOSAL FOR PUBLIC RELEASE In toxicological and biopharmaceutical studies, to investigate the effect of a compound several increasing dose levels are usually compared with a control. The control may be a neutral control, a placebo, or an active control, a standard drug known to be effective. Therefore, dose-response experiments are often conducted in a one-way layout in which the doses of the compound under consideration are allocated to separate groups of subjects. There are different concerns in these studies. In toxicological studies, the main concern is the safety of the toxin under consideration and the goal is to estimate the highest dose that shows no significant difference from the control. This highest dose is generally called the no statistical significance for trend or no observed adverse event level dose. In pharmaceutical studies, however, the primary goal is to assess whether there is indeed a dose-response effect which means that at least one treatment is effective in comparison to the control. If a dose response effect is found, then to identify the lowest dose level producing a desirable effect over that of the control. This lowest dose level is commonly referred to as the minimum effective dose, the dose that is clinically significantly better than the mean response of the neutral control; that is MED=min{d(i):m(i)>m(0) + c} where c is defined as a clinically significant difference preassigned by an experimenter. For efficacy studies, identifying the minimum effective dose is important since high doses often turn out to have undesirable side effects. The aim of this investigation is to construct most efficient statistical inference procedures for various kind of prior information concerning regression curves.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Newfoundland and Labrador, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
4541-2006
Name nom
Lee, ChuIn(Charles)
Department département
Mathematics and Statistics
Organization id
89
Institution établissement
Memorial University of Newfoundland
Province en
Newfoundland and Labrador
Province fr
Terre-Neuve-et-Labrador
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2006
Competition year année de concours
2006
Award amount
10703
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
1205
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Mathematical sciences
Area of application fr
Sciences mathématiques
Research subject code
3009
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Parametric inference
Research subject fr
Inférence paramétrique
Partie
1
Nb partie
1
Application title
Simultaneous statistical inference under order restrictions and its application to dose-response studies
Keyword
NA
Application summary
SUMMARY OF PROPOSAL FOR PUBLIC RELEASE In toxicological and biopharmaceutical studies, to investigate the effect of a compound several increasing dose levels are usually compared with a control. The control may be a neutral control, a placebo, or an active control, a standard drug known to be effective. Therefore, dose-response experiments are often conducted in a one-way layout in which the doses of the compound under consideration are allocated to separate groups of subjects. There are different concerns in these studies. In toxicological studies, the main concern is the safety of the toxin under consideration and the goal is to estimate the highest dose that shows no significant difference from the control. This highest dose is generally called the no statistical significance for trend or no observed adverse event level dose. In pharmaceutical studies, however, the primary goal is to assess whether there is indeed a dose-response effect which means that at least one treatment is effective in comparison to the control. If a dose response effect is found, then to identify the lowest dose level producing a desirable effect over that of the control. This lowest dose level is commonly referred to as the minimum effective dose, the dose that is clinically significantly better than the mean response of the neutral control; that is MED=min{d(i):m(i)>m(0) + c} where c is defined as a clinically significant difference preassigned by an experimenter. For efficacy studies, identifying the minimum effective dose is important since high doses often turn out to have undesirable side effects. The aim of this investigation is to construct most efficient statistical inference procedures for various kind of prior information concerning regression curves.