Katherine R. Gordon
How Mixed-Effects Modeling Can Advance Our Understanding of Learning and Memory and Improve Clinical and Educational Practice
Boys Town National Research Hospital
purpose key goal researchers clinicians educators within fields speech language hearing sciences support learning memory others consider factors relevant individual material learned training strategy maximize learning retention statistical methods typically used within fields inadequate identifying complex relationships factors ill equipped account variability across individuals identifying relationships specifically traditional statistical methods often inadequate answering questions special populations samples drawn populations usually small highly variable skewed distribution mixedeffects modeling provides advantages traditional statistical techniques answer complex questions taking account common characteristics special populations method results two examples illustrate advantages mixedeffects modeling answering questions learning memory supporting better translation research practice also demonstrate key similarities differences analysis variance regression analyses mixedeffects modeling finally explain three additional advantages using mixedeffects modeling understand processes learning memory means account missing data assess contribution variations delay intervals model nonlinear relationships factors conclusions mixedeffects modeling researchers disseminate accurate information learning memory clinicians educators turn enhanced statistical literacy clinicians educators apply research findings practice confidence overall mixedeffects modeling powerful tool improve outcomes individuals researchers practitioners serve within fields speech language hearing sciences