On the binomial confidence interval and probabilistic robust control

Chen, Xinjia; Zhou, Kemin; Aravena, J.L.

doi:10.1016/j.automatica.2004.04.016

Cited by 3 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All 95% confidence intervals for AFP notification rates include 1 case per 100,000 children aged less than 15 years apart from estimates for Victoria and Western Australia. The exact binomial confidence interval is known to be conservative for rare events [ 45 ]; however, findings were not appreciably different when the score method was used (data not shown). Similarly, 95% confidence intervals for the probability of stool sampling given notification do not include the WHO target rate for all jurisdictions apart from the Australian Capital Territory and Tasmania, which both have wide confidence intervals due to the small number of cases observed.…”

Section: Resultsmentioning

confidence: 99%

An evaluation of the sensitivity of acute flaccid paralysis surveillance for poliovirus infection in Australia

et al. 2009

View full text Add to dashboard Cite

BackgroundWorld Health Organization (WHO) targets for acute flaccid paralysis (AFP) surveillance, including the notification of a minimum rate of AFP among children, are used to assess the adequacy of AFP surveillance for the detection of poliovirus infection. Sensitive surveillance for poliovirus infection in both developed and developing countries is essential to support global disease eradication efforts. We applied recently developed methods for the quantitative evaluation of disease surveillance systems to evaluate the sensitivity of AFP surveillance for poliovirus infection in Australia.MethodsA scenario tree model which accounted for administrative region, age, population immunity, the likelihood of AFP, and the probability of notification and stool sampling was used to assess the sensitivity of AFP surveillance for wild poliovirus infection among children aged less than 15 years in Australia. The analysis was based on historical surveillance data collected between 2000 and 2005. We used a surveillance time period of one month, and evaluated the ability of the surveillance system to detect poliovirus infection at a prevalence of 1 case per 100 000 persons and 1 case per million persons.ResultsThere was considerable variation in the sensitivity of AFP surveillance for poliovirus infection among Australian States and Territories. The estimated median sensitivity of AFP surveillance in Australia among children aged less than 15 years was 8.2% per month at a prevalence of 1 case per 100,000 population, and 0.9% per month at a prevalence of 1 case per million population. The probability that Australia is free from poliovirus infection given negative surveillance findings following 5 years of continuous surveillance was 96.9% at a prevalence of 1 case per 100,000 persons and 56.5% at a prevalence of 1 case per million persons.ConclusionGiven the ongoing risk of poliovirus importation prior to global eradication, long term surveillance is required to provide a high degree of confidence in freedom from poliovirus infection in Australia, particularly if a low prevalence of infection is assumed. Adherence to the WHO surveillance targets would considerably improve the sensitivity of surveillance for poliovirus infection in Australia.

show abstract

Section: Resultsmentioning

confidence: 99%

An evaluation of the sensitivity of acute flaccid paralysis surveillance for poliovirus infection in Australia

et al. 2009

View full text Add to dashboard Cite

show abstract

“…Consider the binomial case d = 2 for which p = (p 1 , 1 − p 1 ). The well known Clopper-Pearson interval for p 1 relies on the exact distribution of X 1 in the binomial case [14,20,13]. It was considered for a long time as outstanding.…”

Section: The Clopper-pearson Regionsmentioning

confidence: 99%

Confidence Regions for the Multinomial Parameter With Small Sample Size

Chafäı

Concordet

2009

Journal of the American Statistical Association

View full text Add to dashboard Cite

Consider the observation of n iid realizations of an experiment with d ≥ 2 possible outcomes, which corresponds to a single observation of a multinomial distribution M d (n, p) where p is an unknown discrete distribution on {1, . . . , d}. In many applications, the construction of a confidence region for p when n is small is crucial. This concrete challenging problem has a long history. It is well known that the confidence regions built from asymptotic statistics do not have good coverage when n is small. On the other hand, most available methods providing non-asymptotic regions with controlled coverage are limited to the binomial case d = 2. In the present work, we propose a new method valid for any d ≥ 2. This method provides confidence regions with controlled coverage and small volume, and consists of the inversion of the "covering collection" associated with level-sets of the likelihood. The behavior when d/n tends to infinity remains an interesting open problem beyond the scope of this work.

show abstract

Binomial and Poisson Confidence Intervals and Its Variants: A Bibliography

Khurshid¹

2010

Pak.j.stat.oper.res.

View full text Add to dashboard Cite

show abstract

On the binomial confidence interval and probabilistic robust control

Cited by 3 publications

References 22 publications

An evaluation of the sensitivity of acute flaccid paralysis surveillance for poliovirus infection in Australia

An evaluation of the sensitivity of acute flaccid paralysis surveillance for poliovirus infection in Australia

Confidence Regions for the Multinomial Parameter With Small Sample Size

Binomial and Poisson Confidence Intervals and Its Variants: A Bibliography

Contact Info

Product

Resources

About