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10.1093/abt/tbab013 http://scihub22266oqcxt.onion/10.1093/abt/tbab013 34286216!8287637!34286216     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Antib+Ther 2021 ; 4 (3): 144-148 Nephropedia Template TP {{tp|p=34286216|t=2021. Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection |pdf=|usr=}}{{34286216}} gab.com Text Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection JO: Antib Ther http://www.kidney.de/pget.php?&tw=1&pmid=34286216 #FOAvip The duration of natural immunity in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a matter of some debate in the literature at present. For example, in a recent publication characterizing SARS-CoV-2 immunity over time, the authors fit pooled longitudinal data, using fitted slopes to infer the duration of SARS-CoV-2 immunity. In fact, such approaches can lead to misleading conclusions as a result of statistical model-fitting artifacts. To exemplify this phenomenon, we reanalyzed one of the markers (pseudovirus neutralizing titer) in the publication, using mixed-effects modeling, a methodology better suited to longitudinal datasets like these. Our findings showed that the half-life was both longer and more variable than reported by the authors. The example selected by us here illustrates the utility of mixed-effects modeling in provide more accurate estimates of the duration and heterogeneity of half-lives of molecular and cellular biomarkers of SARS-CoV-2 immunity. Twit Text FOAVip Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection ????Antib Ther http://www.kidney.de/pget.php?&tw=1&pmid=34286216 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34286216 #FOAvip English Wikipedia <ref>{{Cite pmid|34286216}}</ref> Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection #MMPMID34286216 Bottino D; Hather G; Yuan L; Stoddard M; White L; Chakravarty A Antib Ther 2021[Jul]; 4 (3): 144-148 PMID34286216show ga The duration of natural immunity in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a matter of some debate in the literature at present. For example, in a recent publication characterizing SARS-CoV-2 immunity over time, the authors fit pooled longitudinal data, using fitted slopes to infer the duration of SARS-CoV-2 immunity. In fact, such approaches can lead to misleading conclusions as a result of statistical model-fitting artifacts. To exemplify this phenomenon, we reanalyzed one of the markers (pseudovirus neutralizing titer) in the publication, using mixed-effects modeling, a methodology better suited to longitudinal datasets like these. Our findings showed that the half-life was both longer and more variable than reported by the authors. The example selected by us here illustrates the utility of mixed-effects modeling in provide more accurate estimates of the duration and heterogeneity of half-lives of molecular and cellular biomarkers of SARS-CoV-2 immunity. äUsing mixed-effects modeling to estimate decay kinetics of response to(epmc).pdf DeepDyve Pubget Overpricing