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10.1111/biom.12543 http://scihub22266oqcxt.onion/10.1111/biom.12543 C5106349!5106349 !27167143     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 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\27167143 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Biometrics 2017 ; 73 (1 ): 156-166 Nephropedia Template TP {{tp|p=27167143 |t=2017. Alternative measures of between-study heterogeneity in meta-analysis: Reducing the impact of outlying studies |pdf=|usr=}}{{27167143 }} gab.com Text Alternative measures of between-study heterogeneity in meta-analysis: Reducing the impact of outlying studies JO: Biometrics http://www.kidney.de/pget.php?&tw=1&pmid=27167143 #FOAvip Meta-analysis has become a widely used tool to combine results from independent studies. The collected studies are homogeneous if they share a common underlying true effect size; otherwise, they are heterogeneous. A fixed-effect model is customarily used when the studies are deemed homogeneous, while a random-effects model is used for heterogeneous studies. Assessing heterogeneity in meta-analysis is critical for model selection and decision making. Ideally, if heterogeneity is present, it should permeate the entire collection of studies, instead of being limited to a small number of outlying studies. Outliers can have great impact on conventional measures of heterogeneity and the conclusions of a meta-analysis. However, no widely accepted guidelines exist for handling outliers. This article proposes several new heterogeneity measures. In the presence of outliers, the proposed measures are less affected than the conventional ones. The performance of the proposed and conventional heterogeneity measures are compared theoretically, by studying their asymptotic properties, and empirically, using simulations and case studies. Twit Text FOAVip Alternative measures of between-study heterogeneity in meta-analysis: Reducing the impact of outlying studies ????Biometrics http://www.kidney.de/pget.php?&tw=1&pmid=27167143 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27167143 #FOAvip English Wikipedia <ref>{{Cite pmid|27167143 }}</ref> Alternative measures of between-study heterogeneity in meta-analysis: Reducing the impact of outlying studies #MMPMID27167143 Lin L ; Chu H ; Hodges JS Biometrics 2017[Mar]; 73 (1 ): 156-166 PMID27167143 show ga Meta-analysis has become a widely used tool to combine results from independent studies. The collected studies are homogeneous if they share a common underlying true effect size; otherwise, they are heterogeneous. A fixed-effect model is customarily used when the studies are deemed homogeneous, while a random-effects model is used for heterogeneous studies. Assessing heterogeneity in meta-analysis is critical for model selection and decision making. Ideally, if heterogeneity is present, it should permeate the entire collection of studies, instead of being limited to a small number of outlying studies. Outliers can have great impact on conventional measures of heterogeneity and the conclusions of a meta-analysis. However, no widely accepted guidelines exist for handling outliers. This article proposes several new heterogeneity measures. In the presence of outliers, the proposed measures are less affected than the conventional ones. The performance of the proposed and conventional heterogeneity measures are compared theoretically, by studying their asymptotic properties, and empirically, using simulations and case studies. |*Analysis of Variance [MESH] |*Data Interpretation, Statistical [MESH] |*Meta-Analysis as Topic [MESH] |Aged [MESH] |Computer Simulation [MESH] |Exercise [MESH] |Female [MESH] |Hip Fractures/mortality [MESH] |Humans [MESH] |Intra-Abdominal Fat [MESH] |Male [MESH]Alternative measures of between-study heterogeneity in meta-analysis: (epmc).pdf DeepDyve Pubget Overpricing