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10.1080/03610926.2012.681418 http://scihub22266oqcxt.onion/10.1080/03610926.2012.681418 C4796759!4796759!26997746     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Commun+Stat+Theory+Methods 2014 ; 43 (9): 1979-90 Nephropedia Template TP {{tp|p=26997746|t=2014. A Smooth Bootstrap Procedure towards Deriving Confidence Intervals for the Relative Risk |pdf=|usr=}}{{26997746}} gab.com Text A Smooth Bootstrap Procedure towards Deriving Confidence Intervals for the Relative Risk JO: Commun Stat Theory Methods http://www.kidney.de/pget.php?&tw=1&pmid=26997746 #FOAvip Given a pair of sample estimators of two independent proportions, bootstrap methods are a common strategy towards deriving the associated confidence interval for the relative risk. We develop a new smooth bootstrap procedure, which generates pseudo-samples from a continuous quantile function. Under a variety of settings, our simulation studies show that our method possesses a better or equal performance in comparison with asymptotic theory based and existing bootstrap methods, particularly for heavily unbalanced data in terms of coverage probability and power. We illustrate our procedure as applied to several published data sets. Twit Text FOAVip A Smooth Bootstrap Procedure towards Deriving Confidence Intervals for the Relative Risk ????Commun Stat Theory Methods http://www.kidney.de/pget.php?&tw=1&pmid=26997746 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26997746 #FOAvip English Wikipedia <ref>{{Cite pmid|26997746}}</ref> A Smooth Bootstrap Procedure towards Deriving Confidence Intervals for the Relative Risk #MMPMID26997746 WANG D; HUTSON AD Commun Stat Theory Methods 2014[]; 43 (9): 1979-90 PMID26997746show ga Given a pair of sample estimators of two independent proportions, bootstrap methods are a common strategy towards deriving the associated confidence interval for the relative risk. We develop a new smooth bootstrap procedure, which generates pseudo-samples from a continuous quantile function. Under a variety of settings, our simulation studies show that our method possesses a better or equal performance in comparison with asymptotic theory based and existing bootstrap methods, particularly for heavily unbalanced data in terms of coverage probability and power. We illustrate our procedure as applied to several published data sets. äA Smooth Bootstrap Procedure towards Deriving Confidence Intervals for(epmc).pdf DeepDyve Pubget Overpricing