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10.1177/1176934317713004 http://scihub22266oqcxt.onion/10.1177/1176934317713004 C5582720!5582720!28894352     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28894352&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Evol+Bioinform+Online 2017 ; 13 (ä): ä Nephropedia Template TP {{tp|p=28894352|t=2017. Hierarchical Association Coefficient Algorithm: New Method for Genome-Wide Association Study |pdf=|usr=}}{{28894352}} gab.com Text Hierarchical Association Coefficient Algorithm: New Method for Genome-Wide Association Study JO: Evol Bioinform Online http://www.kidney.de/pget.php?&tw=1&pmid=28894352 #FOAvip Hierarchical association coefficient algorithm calculates the degree of association between observations and categories into a value named hierarchical association coefficient (HA-coefficient) between 0 for the lower limit and 1 for the upper limit. The HA-coefficient algorithm can be operated with stratified ascending categories based on the average of observations in each category. The upper limit refers to a condition where observations are increasingly ordered into the stratified ascending categories, whereas the lower limit refers to a condition where observations are decreasingly ordered into the stratified ascending categories. An HA-coefficient represents how close an observed categorization is to the upper limit, or how distant an observed categorization is from the lower limit. To demonstrate robustness and reliability, the HA-coefficient algorithm was applied to 3 different simulated data sets with the same pattern in terms of the association between observations and categories. From all simulated data sets, the same result was obtained, indicating that the HA-coefficient algorithm is robust and reliable. Twit Text FOAVip Hierarchical Association Coefficient Algorithm: New Method for Genome-Wide Association Study ????Evol Bioinform Online http://www.kidney.de/pget.php?&tw=1&pmid=28894352 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28894352 #FOAvip English Wikipedia <ref>{{Cite pmid|28894352}}</ref> Hierarchical Association Coefficient Algorithm: New Method for Genome-Wide Association Study #MMPMID28894352 Kim B Evol Bioinform Online 2017[]; 13 (ä): ä PMID28894352show ga Hierarchical association coefficient algorithm calculates the degree of association between observations and categories into a value named hierarchical association coefficient (HA-coefficient) between 0 for the lower limit and 1 for the upper limit. The HA-coefficient algorithm can be operated with stratified ascending categories based on the average of observations in each category. The upper limit refers to a condition where observations are increasingly ordered into the stratified ascending categories, whereas the lower limit refers to a condition where observations are decreasingly ordered into the stratified ascending categories. An HA-coefficient represents how close an observed categorization is to the upper limit, or how distant an observed categorization is from the lower limit. To demonstrate robustness and reliability, the HA-coefficient algorithm was applied to 3 different simulated data sets with the same pattern in terms of the association between observations and categories. From all simulated data sets, the same result was obtained, indicating that the HA-coefficient algorithm is robust and reliable. äHierarchical Association Coefficient Algorithm: New Method for Genome-(epmc).pdf DeepDyve Pubget Overpricing