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10.1111/biom.12659 http://scihub22266oqcxt.onion/10.1111/biom.12659 C5550375!5550375!28182835     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biometrics 2017 ; 73 (3): 916-26 Nephropedia Template TP {{tp|p=28182835|t=2017. Maximin Optimal Designs for Cluster Randomized Trials |pdf=|usr=}}{{28182835}} gab.com Text Maximin Optimal Designs for Cluster Randomized Trials JO: Biometrics http://www.kidney.de/pget.php?&tw=1&pmid=28182835 #FOAvip We consider design issues for cluster randomized trials (CRTs) with a binary outcome where both unit costs and intraclass correlation coefficients (ICCs) in the two arms may be unequal. We first propose a design that maximizes cost efficiency (CE), defined as the ratio of the precision of the efficacy measure to the study cost. Because such designs can be highly sensitive to the unknown ICCs and the anticipated success rates in the two arms, a local strategy based on a single set of best guesses for the ICCs and success rates can be risky. To mitigate this issue, we propose a maximin optimal design that permits ranges of values to be specified for the success rate and the ICC in each arm. We derive maximin optimal designs for three common measures of the efficacy of the intervention, risk difference, relative risk and odds ratio, and study their properties. Using a real cancer control and prevention trial example, we ascertain the efficiency of the widely used balanced design relative to the maximin optimal design and show that the former can be quite inefficient and less robust to mis-specifications of the ICCs and the success rates in the two arms. Twit Text FOAVip Maximin Optimal Designs for Cluster Randomized Trials ????Biometrics http://www.kidney.de/pget.php?&tw=1&pmid=28182835 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28182835 #FOAvip English Wikipedia <ref>{{Cite pmid|28182835}}</ref> Maximin Optimal Designs for Cluster Randomized Trials #MMPMID28182835 Wu S; Wong WK; Crespi CM Biometrics 2017[Sep]; 73 (3): 916-26 PMID28182835show ga We consider design issues for cluster randomized trials (CRTs) with a binary outcome where both unit costs and intraclass correlation coefficients (ICCs) in the two arms may be unequal. We first propose a design that maximizes cost efficiency (CE), defined as the ratio of the precision of the efficacy measure to the study cost. Because such designs can be highly sensitive to the unknown ICCs and the anticipated success rates in the two arms, a local strategy based on a single set of best guesses for the ICCs and success rates can be risky. To mitigate this issue, we propose a maximin optimal design that permits ranges of values to be specified for the success rate and the ICC in each arm. We derive maximin optimal designs for three common measures of the efficacy of the intervention, risk difference, relative risk and odds ratio, and study their properties. Using a real cancer control and prevention trial example, we ascertain the efficiency of the widely used balanced design relative to the maximin optimal design and show that the former can be quite inefficient and less robust to mis-specifications of the ICCs and the success rates in the two arms. äMaximin Optimal Designs for Cluster Randomized Trials (epmc).pdf DeepDyve Pubget Overpricing