Statistical distribution of the difference of two proportions

Nadarajah, Saralees; Kotz, Samuel

doi:10.1002/sim.2701

Cited by 11 publications

(16 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the literature, several papers deal with these problems in different contexts. [7][8][9][10][11][12][13][14][15][16] The current paper extends existing work in several important ways. First, we present in a single package the computer programs developed in R 17 to perform exact probability calculations for the described measures of the treatment effect.…”

Section: Introductionmentioning

confidence: 94%

Exact Bayesian Inference Comparing Binomial Proportions, With Application to Proof-of-Concept Clinical Trials

Sverdlov¹,

Ryeznik

2015

Ther Innov Regul Sci

View full text Add to dashboard Cite

The authors revisit the problem of exact Bayesian inference comparing two independent binomial proportions. Numerical integration in R is used to compute exact posterior distribution functions, probability densities, and quantiles of the risk difference, relative risk, and odds ratio. An application of the methodology is given in the context of randomized comparative proof-of-concept clinical trials that are driven by evaluation of quantitative criteria combining statistical significance and clinical relevance. A two-stage adaptive design based on predictive probability of success is proposed and its operating characteristics are studied via Monte Carlo simulation. The authors conclude that exact Bayesian methods provide an elegant and efficient way to facilitate design and analysis of proof-of-concept studies.

show abstract

Section: Introductionmentioning

confidence: 94%

Exact Bayesian Inference Comparing Binomial Proportions, With Application to Proof-of-Concept Clinical Trials

Sverdlov¹,

Ryeznik

2015

Ther Innov Regul Sci

View full text Add to dashboard Cite

show abstract

“…Still, while these hazard ratios offer a purer perspective on underlying effects playing primarily on one type of outcome, their meaning is hard to operationalize and often leads to confusion 41–43.…”

Section: The Swedish Riksstroke Registrymentioning

confidence: 99%

Evaluating hospital performance based on excess cause‐specific incidence

Rompaye

Eriksson

Goetghebeur

2015

Statistics in Medicine

View full text Add to dashboard Cite

Formal evaluation of hospital performance in specific types of care is becoming an indispensable tool for quality assurance in the health care system. When the prime concern lies in reducing the risk of a cause-specific event, we propose to evaluate performance in terms of an average excess cumulative incidence, referring to the center's observed patient mix. Its intuitive interpretation helps give meaning to the evaluation results and facilitates the determination of important benchmarks for hospital performance. We apply it to the evaluation of cerebrovascular deaths after stroke in Swedish stroke centers, using data from Riksstroke, the Swedish stroke registry. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

show abstract

“…Marshall (1988) extended the results of OR by using hypergeometric functions (Gauss 1813) to allow the hyperparameters being any positive numbers. Nadarajah and Kotz (2007) gave a formula for RD using Appell hypergeometric function. Chen and Luo (2011) corrected the formula by Nadarajah and Kotz (2007) and further simplified the formula to avoid divergence of the Appell hypergeometric function.…”

Section: Introductionmentioning

confidence: 99%

“…Nadarajah and Kotz (2007) gave a formula for RD using Appell hypergeometric function. Chen and Luo (2011) corrected the formula by Nadarajah and Kotz (2007) and further simplified the formula to avoid divergence of the Appell hypergeometric function. Hora and Kelley (1983) and Hashemi et al (1997) extended the results of Nurminen and Mutanen (1987) on RR to beta prior distributions with any positive hyperparameters.…”

Section: Introductionmentioning

confidence: 99%