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10.1177/1740774514547397 http://scihub22266oqcxt.onion/10.1177/1740774514547397 C4229398!4229398!25179541     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Clin+Trials 2014 ; 11 (6): 657-66 Nephropedia Template TP {{tp|p=25179541|t=2014. Effective sample size for computing prior hyperarameters in Bayesian phase I-II dose-finding |pdf=|usr=}}{{25179541}} gab.com Text Effective sample size for computing prior hyperarameters in Bayesian phase I-II dose-finding JO: Clin Trials http://www.kidney.de/pget.php?&tw=1&pmid=25179541 #FOAvip Background: The efficacy-toxicity trade-off based design is a practical Bayesian phase I-II dose-finding methodology. Because the design's performance is very sensitive to prior hyperparameters and the shape of the target trade-off contour, specifying these two design elements properly is essential. Purpose: The goals are to provide a method that uses elicited mean outcome probabilities to derive a prior that is neither overly informative nor overly disperse, and practical guidelines for specifying the target trade-off contour. Methods: A general algorithm is presented that determines prior hyperpameters using least squares penalized by effective sample size. Guidelines for specifying the trade-off contour are provided. These methods are illustrated by a clinical trial in advanced prostate cancer. A new version of the EffTox program is provided for implementation. Results: Together, the algorithm and guidelines provide substantive improvements in the design's operating characteristics. Limitations: The method requires a substantial number of elicited values and design parameters, and computer simulations are required to obtain an acceptable design. Conclusions: The two key improvements greatly enhance the EffTox design's practical usefulness and are straightforward to implement using the updated computer program. The algorithm for determining prior hyperparameters to ensure a specified level of informativeness is general, and may be applied to models other than that underlying the EffTox method. Twit Text FOAVip Effective sample size for computing prior hyperarameters in Bayesian phase I-II dose-finding ????Clin Trials http://www.kidney.de/pget.php?&tw=1&pmid=25179541 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25179541 #FOAvip English Wikipedia <ref>{{Cite pmid|25179541}}</ref> Effective sample size for computing prior hyperarameters in Bayesian phase I-II dose-finding #MMPMID25179541 Thall PF; Herrick RC; Nguyen HQ; Venier JJ; Norris JC Clin Trials 2014[Dec]; 11 (6): 657-66 PMID25179541show ga Background: The efficacy-toxicity trade-off based design is a practical Bayesian phase I-II dose-finding methodology. Because the design's performance is very sensitive to prior hyperparameters and the shape of the target trade-off contour, specifying these two design elements properly is essential. Purpose: The goals are to provide a method that uses elicited mean outcome probabilities to derive a prior that is neither overly informative nor overly disperse, and practical guidelines for specifying the target trade-off contour. Methods: A general algorithm is presented that determines prior hyperpameters using least squares penalized by effective sample size. Guidelines for specifying the trade-off contour are provided. These methods are illustrated by a clinical trial in advanced prostate cancer. A new version of the EffTox program is provided for implementation. Results: Together, the algorithm and guidelines provide substantive improvements in the design's operating characteristics. Limitations: The method requires a substantial number of elicited values and design parameters, and computer simulations are required to obtain an acceptable design. Conclusions: The two key improvements greatly enhance the EffTox design's practical usefulness and are straightforward to implement using the updated computer program. The algorithm for determining prior hyperparameters to ensure a specified level of informativeness is general, and may be applied to models other than that underlying the EffTox method. äEffective sample size for computing prior hyperarameters in Bayesian p(epmc).pdf DeepDyve Pubget Overpricing