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10.1016/j.beth.2016.12.005 http://scihub22266oqcxt.onion/10.1016/j.beth.2016.12.005 C5458623!5458623!28577591     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Behav+Ther 2017 ; 48 (4): 567-80 Nephropedia Template TP {{tp|p=28577591|t=2017. Implementing Clinical Research Using Factorial Designs: A Primer |pdf=|usr=}}{{28577591}} gab.com Text Implementing Clinical Research Using Factorial Designs: A Primer JO: Behav Ther http://www.kidney.de/pget.php?&tw=1&pmid=28577591 #FOAvip Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers? increased and careful execution of such designs. Twit Text FOAVip Implementing Clinical Research Using Factorial Designs: A Primer ????Behav Ther http://www.kidney.de/pget.php?&tw=1&pmid=28577591 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28577591 #FOAvip English Wikipedia <ref>{{Cite pmid|28577591}}</ref> Implementing Clinical Research Using Factorial Designs: A Primer #MMPMID28577591 Baker TB; Smith SS; Bolt DM; Loh WY; Mermelstein R; Fiore MC; Piper ME; Collins LM Behav Ther 2017[Jul]; 48 (4): 567-80 PMID28577591show ga Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers? increased and careful execution of such designs. äImplementing Clinical Research Using Factorial Designs: A Primer (epmc).pdf DeepDyve Pubget Overpricing