02449oam 2200673 450 991070788670332120170322084715.0(CKB)5470000002467688(OCoLC)55500042(EXLCZ)99547000000246768820040527j200102 ua 0engurmn|||||||||txtrdacontentcrdamediacrrdacarrierMicrogravity combustion science and fluid physics experiments and facilities for the ISS /Richard W. Lauver [and five others]Cleveland, Ohio :National Aeronautics and Space Administration, Glenn Research Center,February 2001.1 online resource (17 pages) illustrationsNASA/TM ;2001-210202"February 2001.""Prepared for the Spacebound 2000 sponsored by the Canadian Space Agency, Vancouver, British Columbia, Canada, May 15-18, 2000.""Performing organization: National Aeronautics and Space Administration, John H. Glenn Research Center at Lewis Field"--Report documentation page.Includes bibliographical references (pages 16-17).Microgravity combustion science and fluid physics experiments and facilities for the International Space StationCombustionfastCombustion engineeringfastJetsFluid dynamicsfastSpace stationsfastCombustion physicsnasatFluid dynamicsnasatGas jetsnasatJet flownasatMicrogravitynasatFlammabilitynasatCombustion.Combustion engineering.JetsFluid dynamics.Space stations.Combustion physics.Fluid dynamics.Gas jets.Jet flow.Microgravity.Flammability.Lauver Richard W.1421075Canadian Space Agency.NASA Glenn Research Center,BUFBUFOCLCQOCLCFOCLCOOCLCQGPOBOOK9910707886703321Microgravity combustion science and fluid physics experiments and facilities for the ISS3541275UNINA04672nam 2201057z- 450 991055760810332120220321(CKB)5400000000045321(oapen)https://directory.doabooks.org/handle/20.500.12854/79674(oapen)doab79674(EXLCZ)99540000000004532120202203d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierBayesian Design in Clinical TrialsBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (190 p.)3-0365-3333-8 In the last decade, the number of clinical trials using Bayesian methods has grown dramatically. Nowadays, regulatory authorities appear to be more receptive to Bayesian methods than ever. The Bayesian methodology is well suited to address the issues arising in the planning, analysis, and conduct of clinical trials. Due to their flexibility, Bayesian design methods based on the accrued data of ongoing trials have been recommended by both the US Food and Drug Administration and the European Medicines Agency for dose-response trials in early clinical development. A distinctive feature of the Bayesian approach is its ability to deal with external information, such as historical data, findings from previous studies and expert opinions, through prior elicitation. In fact, it provides a framework for embedding and handling the variability of auxiliary information within the planning and analysis of the study. A growing body of literature examines the use of historical data to augment newly collected data, especially in clinical trials where patients are difficult to recruit, which is the case for rare diseases, for example. Many works explore how this can be done properly, since using historical data has been recognized as less controversial than eliciting prior information from experts' opinions. In this book, applications of Bayesian design in the planning and analysis of clinical trials are introduced, along with methodological contributions to specific topics of Bayesian statistics. Finally, two reviews regarding the state-of-the-art of the Bayesian approach in clinical field trials are presented.HumanitiesbicsscSocial interactionbicsscadaptive designsadaptive randomizationBayesianBayesian designsbayesian inferenceBayesian inferencebayesian meta-analysisBayesian monitoringBayesian trialBayesian trial designbinary databridging studiescausal inferencecisplatinclinical trialclinical trialsclusteringcombination studydistribution distancedose escalationdose-escalationdose-findingdose-responsedoubly robust estimationdoxorubicinearly phase dose findingfrequentist validationfutility ruleshighest posterior density intervalsinteractioninterim analysislatent dirichlet allocationmeta-analysismodelling assumptionnormal approximationoncologyoptimal dose combinationoxaliplatinperitoneal carcinomatosisphase IPIPACpoor accrualposterior and predictive probabilitiespower-priorpredictive analysispredictive powerprior distributionprior elicitationpriorspropensity scorerandomized controlled trialrare diseasesample sizesample size determinationstopping boundariestarget allocationtreatment combinationsHumanitiesSocial interactionBerchialla Paolaedt1325099Baldi IleanaedtBerchialla PaolaothBaldi IleanaothBOOK9910557608103321Bayesian Design in Clinical Trials3036577UNINA