A Minimum-Cost Strategy for Cluster Recruitment
It is becoming increasingly common for the design of a clinical study to involve cluster samples. Very few researches investigated the appropriate number of clusters. None of them treat cluster size and the number of clusters as random variables. In reality, the recruitment of clusters can not be re...
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| Veröffentlicht in: | Biometrical journal 2000-11, Vol.42 (7), p.877-886 |
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| creator | Chan, Wenyaw Peng, Nan Fu |
| description | It is becoming increasingly common for the design of a clinical study to involve cluster samples. Very few researches investigated the appropriate number of clusters. None of them treat cluster size and the number of clusters as random variables. In reality, the recruitment of clusters can not be reached at one time and the cluster sizes are usually random. The longer the recruitment takes the more expensive the total study costs will be. This paper provides a strategy for sequential recruitment of clusters, which can minimize the total study cost. By treating the number of additional observational subjects required at each time point as a Markov Chain, we derive an iterative procedure for optimal strategy and study the property of this strategy, especially the duration of the cluster recruitment. This strategy is also extended to search for an optimal number of centers in a multi‐center clinical trial. |
| doi_str_mv | 10.1002/1521-4036(200011)42:7<877::AID-BIMJ877>3.0.CO;2-C |
| format | Article |
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This strategy is also extended to search for an optimal number of centers in a multi‐center clinical trial.</description><subject>Cluster sample</subject><subject>Exact sciences and technology</subject><subject>Inference from stochastic processes; time series analysis</subject><subject>Markov chain</subject><subject>Mathematics</subject><subject>Multivariate analysis</subject><subject>Principle of optimality</subject><subject>Probability and statistics</subject><subject>Probability theory and stochastic processes</subject><subject>Sciences and techniques of general use</subject><subject>Sequential method</subject><subject>Sequential methods</subject><subject>Statistics</subject><subject>Stochastic processes</subject><issn>0323-3847</issn><issn>1521-4036</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><recordid>eNqVkN9v0zAQxy0EEmXwP0RCQvDg7ny266QgpBLYKFpXjV97PDmeg8KSZtiJoP_9XLX0iReeTne6-3x1H8YKAVMBgKdCo-AK5OwlAoAQrxTOzZvcmPl8sXzP3y1Xn1LzVk5hWq5fIy8fsMnx5iGbgETJZa7MY_Ykxp-JUYDCCTtdZKtm03Rjx8s-DtmXIdjB_9hmdR-ysh3j4EP22bswNkPnN8NT9qi2bfTPDvWEfTv78LX8yC_W58tyccGdAjQcFWqp7Y2DaqZtbpyvVKW0QKhvaoPOg8y9RyOs1EbMauXSvNaVzwupoEJ5wl7suXeh_zX6OFDXROfb1m58P0ZCIUDqQqXFq_2iC32Mwdd0F5rOhi0JoJ062mmgnQbaqyOFZCjZIkrq6KCOJAGVa0IqE_P5IdxGZ9s62I1r4hGcCyUKKY-v_25av_2P2H-n_h0lLt9zmyT_z5Frwy3NjDSari_PCa-NWH2HdCXvAQW6mVM</recordid><startdate>200011</startdate><enddate>200011</enddate><creator>Chan, Wenyaw</creator><creator>Peng, Nan Fu</creator><general>WILEY-VCH Verlag Berlin GmbH</general><general>WILEY‐VCH Verlag Berlin GmbH</general><general>Wiley-VCH</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>200011</creationdate><title>A Minimum-Cost Strategy for Cluster Recruitment</title><author>Chan, Wenyaw ; Peng, Nan Fu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4027-242535adc0b65a87ceb4b45120fdf72ce038ee271a35716f4cfdff5be89340b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Cluster sample</topic><topic>Exact sciences and technology</topic><topic>Inference from stochastic processes; time series analysis</topic><topic>Markov chain</topic><topic>Mathematics</topic><topic>Multivariate analysis</topic><topic>Principle of optimality</topic><topic>Probability and statistics</topic><topic>Probability theory and stochastic processes</topic><topic>Sciences and techniques of general use</topic><topic>Sequential method</topic><topic>Sequential methods</topic><topic>Statistics</topic><topic>Stochastic processes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chan, Wenyaw</creatorcontrib><creatorcontrib>Peng, Nan Fu</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Biometrical journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chan, Wenyaw</au><au>Peng, Nan Fu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Minimum-Cost Strategy for Cluster Recruitment</atitle><jtitle>Biometrical journal</jtitle><addtitle>Biom. 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| ispartof | Biometrical journal, 2000-11, Vol.42 (7), p.877-886 |
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| language | eng |
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| source | Wiley Online Library All Journals |
| subjects | Cluster sample Exact sciences and technology Inference from stochastic processes time series analysis Markov chain Mathematics Multivariate analysis Principle of optimality Probability and statistics Probability theory and stochastic processes Sciences and techniques of general use Sequential method Sequential methods Statistics Stochastic processes |
| title | A Minimum-Cost Strategy for Cluster Recruitment |
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