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10.11919/j.issn.1002-0829.216081 http://scihub22266oqcxt.onion/10.11919/j.issn.1002-0829.216081 C5434286!5434286!28638204     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Shanghai+Arch+Psychiatry ä ; 28 (5): 293-300 Nephropedia Template TP {{tp|p=28638204|t=ä. Modern methods for longitudinal data analysis, capabilities, caveats and cautions |pdf=|usr=}}{{28638204}} gab.com Text Modern methods for longitudinal data analysis, capabilities, caveats and cautions JO: Shanghai Arch Psychiatry http://www.kidney.de/pget.php?&tw=1&pmid=28638204 #FOAvip Longitudinal studies are used in mental health research and services studies. The dominant approaches for longitudinal data analysis are the generalized linear mixed-effects models (GLMM) and the weighted generalized estimating equations (WGEE). Although both classes of models have been extensively published and widely applied, differences between and limitations about these methods are not clearly delineated and well documented. Unfortunately, some of the differences and limitations carry significant implications for reporting, comparing and interpreting research findings.In this report, we review both major approaches for longitudinal data analysis and highlight their similarities and major differences. We focus on comparison of the two classes of models in terms of model assumptions, model parameter interpretation, applicability and limitations, using both real and simulated data. We discuss caveats and cautions when applying the two different approaches to real study data. Twit Text FOAVip Modern methods for longitudinal data analysis, capabilities, caveats and cautions ????Shanghai Arch Psychiatry http://www.kidney.de/pget.php?&tw=1&pmid=28638204 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28638204 #FOAvip English Wikipedia <ref>{{Cite pmid|28638204}}</ref> Modern methods for longitudinal data analysis, capabilities, caveats and cautions #MMPMID28638204 GE L; TU JX; ZHANG H; WANG H; HE H; GUNZLER D Shanghai Arch Psychiatry ä[]; 28 (5): 293-300 PMID28638204show ga Longitudinal studies are used in mental health research and services studies. The dominant approaches for longitudinal data analysis are the generalized linear mixed-effects models (GLMM) and the weighted generalized estimating equations (WGEE). Although both classes of models have been extensively published and widely applied, differences between and limitations about these methods are not clearly delineated and well documented. Unfortunately, some of the differences and limitations carry significant implications for reporting, comparing and interpreting research findings.In this report, we review both major approaches for longitudinal data analysis and highlight their similarities and major differences. We focus on comparison of the two classes of models in terms of model assumptions, model parameter interpretation, applicability and limitations, using both real and simulated data. We discuss caveats and cautions when applying the two different approaches to real study data. äModern methods for longitudinal data analysis, capabilities, caveats a(epmc).pdf DeepDyve Pubget Overpricing