Journal Article10.1002/SIM.5947
Sample size calculation for comparing two negative binomial rates.
Haiyuan Zhu,Hassan Lakkis +1 more
100
TL;DR: An explicit formula is developed to calculate sample size based on the negative binomial model and important characteristics of the formula include its accuracy and its ability to explicitly incorporate dispersion parameter and exposure time.
read more
Abstract: Negative binomial model has been increasingly used to model the count data in recent clinical trials. It is frequently chosen over Poisson model in cases of overdispersed count data that are commonly seen in clinical trials. One of the challenges of applying negative binomial model in clinical trial design is the sample size estimation. In practice, simulation methods have been frequently used for sample size estimation. In this paper, an explicit formula is developed to calculate sample size based on the negative binomial model. Depending on different approaches to estimate the variance under null hypothesis, three variations of the sample size formula are proposed and discussed. Important characteristics of the formula include its accuracy and its ability to explicitly incorporate dispersion parameter and exposure time. The performance of the formula with each variation is assessed using simulations.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Ferric carboxymaltose for iron deficiency at discharge after acute heart failure: a multicentre, double-blind, randomised, controlled trial.
Piotr Ponikowski,Bridget-Anne Kirwan,Bridget-Anne Kirwan,Stefan D. Anker,Theresa McDonagh,Theresa McDonagh,Maria Dorobantu,Jarosław Drożdż,Vincent Fabien,Gerasimos Filippatos,Udo Michael Göhring,Andre Keren,Irakli Khintibidze,Hans Kragten,Felipe Martinez,Marco Metra,Davor Miličić,Jose C. Nicolau,Marcus Ohlsson,Alexander Parkhomenko,Domingo A. Pascual-Figal,Frank Ruschitzka,David Sim,Hadi Skouri,Peter van der Meer,Basil S. Lewis,Josep Comin-Colet,Stephan von Haehling,Alain Cohen-Solal,Nicolas Danchin,Wolfram Doehner,Henry J. Dargie,Michael Motro,Javed Butler,Tim Friede,Klaus H Jensen,Stuart Pocock,Ewa A. Jankowska,G Azize,A Fernandez,GO Zapata,P Garcia Pacho,A Glenny,F Ferre Pacora,ML Parody,J Bono,C Beltrano,A Hershson,N Vita,HA Luquez,HG Cestari,H Fernandez,A Prado,M Berli,R García Durán,J Thierer,M Diez,L Lobo Marquez,RR Borelli,Má Hominal,Marco Metra,P Ameri,Piergiuseppe Agostoni,A. Salvioni,L Fattore,Edoardo Gronda,Stefano Ghio,F Turrini,M Uguccioni,M Di Biase,M Piepoli,Stefano Savonitto,A Mortara,P Terrosu,A Fucili,Giuseppe Boriani,P Midi,Enrico Passamonti,F Cosmi,P van der Meer,P Van Bergen,M van de Wetering,Nyy Al-Windy,Wilco Tanis,M Meijs,Rgej Groutars,Bas L.J.H. Kietselaer,Ham van Kesteren,Dpw Beelen,J Heymeriks,R Van de Wal,J Schaap,M Emans,P Westendorp,PR Nierop,R Nijmeijer,Olivier C. Manintveld,M Dorobantu,DA Darabantiu,D Zdrenghea,DM Toader,L Petrescu,Constantin Militaru,D Crisu,MC Tomescu,G Stanciulescu,A Rodica Dan,LC Iosipescu,DL Serban,J Drozdz,J Szachniewicz,M Bronisz,A Tycińska,Beata Wożakowska-Kapłon,E Mirek-Bryniarska,Marcin Gruchała,J Nessler,E Straburzyńska-Migaj,K Mizia-Stec,R Szelemej,R Gil,M Gąsior,Israel Gotsman,Majdi Halabi,Michael Shochat,Michael Shechter,V Witzling,R Zukermann,Y Arbel,M Flugelman,T Ben-Gal,V Zvi,W Kinany,JM Weinstein,Shaul Atar,S Goland,Davor Milicic,D Horvat,S Tušek,M Udovicic,K Šutalo,A Samodol,K Pesek,M Artuković,A Ružić,J Šikić,T McDonagh,J Trevelyan,Y-K Wong,Diana A. Gorog,R Ray,S Pettit,Sanjib Kumar Sharma,A Kabir,H Hamdan,L Tilling,Luciano Moreira Baracioli,L Nigro Maia,Oscar Pereira Dutra,Gilmar Reis,P Pimentel Filho,J.F.K. Saraiva,A Kormann,FR dos Santos,Luiz Carlos Bodanese,D Almeida,Dalton Bertolim Précoma,S Rassi,Fabio T. M. Costa,S.S. Kabbani,K Abdelbaki,C Abdallah,Arnaout,Rabih R. Azar,S Chaaban,O Raed,G Kiwan,B Hassouna,Alfredo Bardají,José Luis Zamorano,S del Prado,JR Gonzalez Juanatey,FI Ga Bosa Ojeda,M Gomez Bueno,BD Molina,DA Pascual Figal,D Sim,TJ Yeo,Sy Loh,D Soon,M Ohlsson,JG Smith,S Gerward,I Khintibidze,Z Lominadze,G Chapidze,N Emukhvari,G Khabeishvili,V Chumburidze,K Paposhvili,T Shaburishvili,O Parhomenko,I Kraiz,O Koval,V Zolotaikina,Y Malynovsky,I Vakaliuk,L Rudenko,V Tseluyko,M Stanislavchuk +209 more
TL;DR: Evaluating the effect of ferric carboxymaltose, compared with placebo, on outcomes in patients who were stabilised after an episode of acute heart failure found no difference in cardiovascular death between the two groups.
617
Effectiveness of a Therapeutic Tai Ji Quan Intervention vs a Multimodal Exercise Intervention to Prevent Falls Among Older Adults at High Risk of Falling: A Randomized Clinical Trial.
Fuzhong Li,Fuzhong Li,Peter Harmer,Kathleen Fitzgerald,Elizabeth Eckstrom,Laura Akers,Li-Shan Chou,Dawna Pidgeon,Jan Voit,Kerri M. Winters-Stone +9 more
TL;DR: Among community-dwelling older adults at high risk for falls, a therapeutically tailored tai ji quan balance training intervention was more effective than conventional exercise approaches for reducing the incidence of falls.
Are young female suicides increasing? A comparison of sex-specific rates and characteristics of youth suicides in Australia over 2004–2014
Nina Stefanac,Sarah E Hetrick,Carol Hulbert,Matthew J Spittal,Katrina Witt,Katrina Witt,Jo Robinson +6 more
TL;DR: Overall, youth suicide rates did not increase significantly in Australia between 2004 and 2014, but there was a significant increase in suicide rates for females, but not males, and the case for a multifaceted prevention approach that capitalize on young females’ greater help-seeking propensity is strengthened.
On the utility of RNA sample pooling to optimize cost and statistical power in RNA sequencing experiments
TL;DR: The results demonstrate that pooling strategies in RNA-seq studies can be both cost-effective and powerful when the number of pools, pool size and sequencing depth are optimally defined.
scPower accelerates and optimizes the design of multi-sample single cell transcriptomic studies.
Katharina T Schmid,Barbara Höllbacher,Cristiana Cruceanu,Anika Böttcher,Heiko Lickert,Elisabeth B. Binder,Elisabeth B. Binder,Fabian J. Theis,Matthias Heinig +8 more
TL;DR: ScPower as mentioned in this paper is a statistical framework for the design and power analysis of multi-sample single cell transcriptomic experiments, which is based on the relationship between sample size, the number of cells per individual, sequencing depth and the power of detecting differentially expressed genes within cell types.
70
References
Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease.
Julie A. Anderson,Bartolome R. Celli,Gary T. Ferguson,Christine Jenkins,Paul W. Jones,Julie C. Yates,Jørgen Vestbo +6 more
TL;DR: The reduction in death from all causes among patients with COPD in the combination-therapy group did not reach the predetermined level of statistical significance, and there were significant benefits in all other outcomes among these patients.
3.3K
•Book
Negative Binomial Regression
Joseph Hilbe
- 01 Jan 2007
TL;DR: In this article, the authors introduce the concept of risk in count response models and assess the performance of count models, including Poisson regression, negative binomial regression, and truncated count models.
Tiotropium in Asthma Poorly Controlled with Standard Combination Therapy
Huib A. M. Kerstjens,Michael Engel,Ronald Dahl,Pierluigi Paggiaro,E Beck,Mark Vandewalker,Ralf Sigmund,Wolfgang Seibold,Petra Moroni-Zentgraf,Eric D. Bateman +9 more
TL;DR: In patients with poorly controlled asthma despite the use of inhaled glucocorticoids and LABAs, the addition of tiotropium significantly increased the time to the first severe exacerbation and provided modest sustained bronchodilation.
Test statistics and sample size formulae for comparative binomial trials with null hypothesis of non-zero risk difference or non-unity relative risk.
TL;DR: This paper reviews some of the test statistics and sample size formulae proposed for comparative binomial trials when the null hypothesis is of a specified non-zero difference or non-unity relative risk.
634