Analysis of a Bayesian repeated measures model for detecting differences in GP prescribing habits
A linear mixed model is used to detect a change, if any, in the prescribing habits in the UK at the general practice (family medicine) level due to an educational intervention given repeated measures data before and after the intervention and a control group. Inferences are corrected for general pra...
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| Veröffentlicht in: | Statistical methods in medical research 2003-12, Vol.12 (6), p.475-487 |
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| container_title | Statistical methods in medical research |
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| creator | Sithole, Jabu S Jones, Peter W |
| description | A linear mixed model is used to detect a change, if any, in the prescribing habits in the UK at the general practice (family medicine) level due to an educational intervention given repeated measures data before and after the intervention and a control group. Inferences are corrected for general practice size and fundholding status. The estimates of the model parameters are obtained using Bayesian inference by applying Gibbs sampling. We develop three different priors for the parameters of the model. These three priors correspond to ‘sceptical,’ ‘reference’ and ‘enthusiastic’ priors in terms of the opinion about the treatment effects that they represent. We compare the results obtained by using these three priors for the parameters in the random effects model. |
| doi_str_mv | 10.1191/0962280203sm320ra |
| format | Article |
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We compare the results obtained by using these three priors for the parameters in the random effects model.</description><subject>Analysis</subject><subject>Anti-Inflammatory Agents, Non-Steroidal - therapeutic use</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Drug Utilization - statistics & numerical data</subject><subject>Drug Utilization - trends</subject><subject>Drugs</subject><subject>Family Practice - education</subject><subject>Family Practice - standards</subject><subject>General practitioners</subject><subject>Humans</subject><subject>Ibuprofen - therapeutic use</subject><subject>Linear Models</subject><subject>Longitudinal Studies</subject><subject>Monte Carlo Method</subject><subject>Practice Patterns, Physicians' - statistics & numerical data</subject><subject>Practice Patterns, Physicians' - trends</subject><subject>Prescribing</subject><subject>Trends</subject><subject>United Kingdom</subject><issn>0962-2802</issn><issn>1477-0334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkUtvFDEQhC0URJbAD8glsnLgNsEejx9zDFEISJHgAOdRj90Ojuaxcc8c9t_Hq10pEhHi0j7UV9W2i7FzKa6kbOVn0Zq6dqIWikZViwxv2EY21lZCqeaEbfZ6tQdO2XuiRyGEFU37jp3KxmiltNwwuJ5g2FEiPkcO_AvskBJMPOMWYcHARwRaMxIf54ADj3PmARf0S5oeeEgxYsbJFz1N_O4n3xbU59Tv1T_Qp4U-sLcRBsKPx_OM_f56--vmW3X_4-77zfV95VXbLFXf6z6Ab4x3wVptQgjRYq2cMiA1YKuik8ZEZcrVowDdBCmdg1ZpY6O36ox9OuRu8_y0Ii3dmMjjMMCE80qdLY9W2qn_gtqK1pVRwMu_wMd5zeW_qKulNa5unCmQPEA-z0QZY7fNaYS866To9i11r1oqnotj8NqPGF4cx1oKcHUACB7wZeu_E58BqUubpg</recordid><startdate>200312</startdate><enddate>200312</enddate><creator>Sithole, Jabu S</creator><creator>Jones, Peter W</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7QJ</scope><scope>7SC</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>HEHIP</scope><scope>JQ2</scope><scope>K9.</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M2S</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>200312</creationdate><title>Analysis of a Bayesian repeated measures model for detecting differences in GP prescribing habits</title><author>Sithole, Jabu S ; Jones, Peter W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c394t-bb5bdac46c8d7756dddf7e23836a15ae93f8166f36653f0a54d1188a93567fc73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Analysis</topic><topic>Anti-Inflammatory Agents, Non-Steroidal - 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| subjects | Analysis Anti-Inflammatory Agents, Non-Steroidal - therapeutic use Bayes Theorem Bayesian analysis Drug Utilization - statistics & numerical data Drug Utilization - trends Drugs Family Practice - education Family Practice - standards General practitioners Humans Ibuprofen - therapeutic use Linear Models Longitudinal Studies Monte Carlo Method Practice Patterns, Physicians' - statistics & numerical data Practice Patterns, Physicians' - trends Prescribing Trends United Kingdom |
| title | Analysis of a Bayesian repeated measures model for detecting differences in GP prescribing habits |
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