SamP2CeT: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials
The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials, where individuals are nested within clusters, for instance patients within general practices. In such two-level cost-effectiveness trials, one can random...
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| Published in | Computational statistics Vol. 34; no. 1; pp. 47 - 70 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.03.2019
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0943-4062 1613-9658 1613-9658 |
| DOI | 10.1007/s00180-018-0829-4 |
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| Abstract | The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials, where individuals are nested within clusters, for instance patients within general practices. In such two-level cost-effectiveness trials, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial). Such trials need careful planning to evaluate the cost-effectiveness of interventions within the available research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. However, the construction of the optimal design requires information on model parameters, which may be unknown at the planning stage of a trial. To overcome this problem, a maximin strategy is employed. We have developed a computer program
SamP2CeT
in R to perform these sample size calculations.
SamP2CeT
provides a graphical user interface which enables the researchers to optimize the numbers of clusters and subjects per cluster in their cost-effectiveness trial as a function of study costs and outcome variances. In case of insufficient knowledge on model parameters,
SamP2CeT
also provides safe numbers of clusters and subjects per cluster, based on a maximin strategy.
SamP2CeT
can be used to calculate the smallest budget needed for a user-specified power level, the largest power attainable with a user-specified budget, and also has the facility to calculate the power for a user-specified design. Recent methodological developments on sample size and power calculation for two-level cost-effectiveness trials have been implemented in
SamP2CeT
. This program is user-friendly, as illustrated for two published cost-effectiveness trials. |
|---|---|
| AbstractList | The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials, where individuals are nested within clusters, for instance patients within general practices. In such two-level cost-effectiveness trials, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial). Such trials need careful planning to evaluate the cost-effectiveness of interventions within the available research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. However, the construction of the optimal design requires information on model parameters, which may be unknown at the planning stage of a trial. To overcome this problem, a maximin strategy is employed. We have developed a computer program
SamP2CeT
in R to perform these sample size calculations.
SamP2CeT
provides a graphical user interface which enables the researchers to optimize the numbers of clusters and subjects per cluster in their cost-effectiveness trial as a function of study costs and outcome variances. In case of insufficient knowledge on model parameters,
SamP2CeT
also provides safe numbers of clusters and subjects per cluster, based on a maximin strategy.
SamP2CeT
can be used to calculate the smallest budget needed for a user-specified power level, the largest power attainable with a user-specified budget, and also has the facility to calculate the power for a user-specified design. Recent methodological developments on sample size and power calculation for two-level cost-effectiveness trials have been implemented in
SamP2CeT
. This program is user-friendly, as illustrated for two published cost-effectiveness trials. The cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials, where individuals are nested within clusters, for instance patients within general practices. In such two-level cost-effectiveness trials, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial). Such trials need careful planning to evaluate the cost-effectiveness of interventions within the available research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. However, the construction of the optimal design requires information on model parameters, which may be unknown at the planning stage of a trial. To overcome this problem, a maximin strategy is employed. We have developed a computer program SamP2CeT in R to perform these sample size calculations. SamP2CeT provides a graphical user interface which enables the researchers to optimize the numbers of clusters and subjects per cluster in their cost-effectiveness trial as a function of study costs and outcome variances. In case of insufficient knowledge on model parameters, SamP2CeT also provides safe numbers of clusters and subjects per cluster, based on a maximin strategy. SamP2CeT can be used to calculate the smallest budget needed for a user-specified power level, the largest power attainable with a user-specified budget, and also has the facility to calculate the power for a user-specified design. Recent methodological developments on sample size and power calculation for two-level cost-effectiveness trials have been implemented in SamP2CeT. This program is user-friendly, as illustrated for two published cost-effectiveness trials. |
| Author | Manju, Md Abu Candel, Math J. J. M. van Breukelen, Gerard J. P. |
| Author_xml | – sequence: 1 givenname: Md Abu orcidid: 0000-0001-8132-9390 surname: Manju fullname: Manju, Md Abu email: abu.manju@maastrichtuniversity.nl organization: Department of Methodology and Statistics, CAPHRI Care and Public Health Research Institute, Maastricht University – sequence: 2 givenname: Math J. J. M. surname: Candel fullname: Candel, Math J. J. M. organization: Department of Methodology and Statistics, CAPHRI Care and Public Health Research Institute, Maastricht University – sequence: 3 givenname: Gerard J. P. surname: van Breukelen fullname: van Breukelen, Gerard J. P. organization: Department of Methodology and Statistics, CAPHRI Care and Public Health Research Institute, Maastricht University |
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| CitedBy_id | crossref_primary_10_1016_j_ajcnut_2023_02_013 crossref_primary_10_1016_j_csda_2020_107143 crossref_primary_10_1080_00220973_2020_1830361 crossref_primary_10_3102_1076998620911916 |
| Cites_doi | 10.3102/10769986028003231 10.1177/0272989X11418372 10.1093/oso/9780199296590.001.0001 10.3758/BRM.40.1.236 10.1177/0962280215569293 10.1161/01.STR.32.7.1684 10.1002/sim.5965 10.1177/0272989X09341752 10.1136/bmj.37942.601331.EE 10.1080/01621459.1985.10478213 10.1037/1082-989X.5.2.199 10.1016/j.spl.2011.02.006 10.1002/hec.1198 10.1177/0962280213511719 10.1177/0272989X98018002S09 10.1002/0470856289 10.1002/hec.914 10.3102/10769986018003237 10.18637/jss.v029.i07 10.1002/sim.6112 10.1136/bmj.a3045 10.1002/9780470746912 10.1037/0033-2909.112.1.155 |
| ContentType | Journal Article |
| Copyright | The Author(s) 2018 Computational Statistics is a copyright of Springer, (2018). All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: The Author(s) 2018 – notice: Computational Statistics is a copyright of Springer, (2018). All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Keywords | Cost-effectiveness analysis Sample size calculation Maximin design Multicentre trials Cluster randomized trials Power Optimal design |
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| References | WillanARBriggsAHStatistical analysis of cost-effectiveness data2006HobokenWiley10.1002/04708562891129.62109 WuCFJEfficient sequential designs with binary dataJ Am Stat Assoc19858597498481960310.1080/01621459.1985.104782130588.62133 RaudenbushSWLiuXStatistical power and optimal design for multisite randomized trialsPsychol Methods20005219921310.1037/1082-989X.5.2.199 SpiegelhalterDJAbramsKRMylesJPBayesian approaches to clinical trials and health-care evaluation2007ChichesterWiley R Development Core Team (2015) R: a language and environment for statistical computing. 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| References_xml | – reference: WuCFJEfficient sequential designs with binary dataJ Am Stat Assoc19858597498481960310.1080/01621459.1985.104782130588.62133 – reference: SculpherMMancaAAbbottJFountainJMasonSGarryRCost effectiveness analysis of laparoscopic hysterectomy compared with standard hysterectomy: results from a randomised trialBr Med J2004328743213413910.1136/bmj.37942.601331.EE – reference: VerbekeGMolenberghsGLinear mixed models for longitudinal data2000New YorkSpringer0956.62055 – reference: WillanARBriggsAHStatistical analysis of cost-effectiveness data2006HobokenWiley10.1002/04708562891129.62109 – reference: BergerMPFWongWKAn introduction to optimal designs for social and bio-medical research2009ChichesterWiley10.1002/9780470746912 – reference: PeaceKChenDGClinical trial data analysis using R2010Boca RatonChapman and Hall – reference: R Development Core Team (2015) R: a language and environment for statistical computing. 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| Title | SamP2CeT: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials |
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