Multiple Regression in L2 Research: A Methodological Synthesis and Guide to Interpreting R2 Values

• DOI: 10.1111/modl.12509
• Publication Date: 2018-09-27T14:15:50Z
• Authors: LUKE PLONSKY; HESSAMEDDIN GHANBAR
• Keywords: Variables

Abstract Multiple regression is a family of statistics used to investigate the relationship between set predictors and criterion (dependent) variable. This procedure applicable in variety research contexts data structures. Consequently, similar quantitative traditions sister‐disciplines such as education psychology (see Skidmore & Thompson, 2010), second language researchers have turned increasingly multiple regression. The present study employs synthetic techniques describe evaluate use this field. Five hundred forty‐one analyses ( K = 171) were coded for different models, variables, procedures, reporting practices, overall variance explained R 2 ). Summary results reveal number inconsistencies (e.g., model types) well lack transparency missing/unreported reliability estimates; see Larson–Hall Plonsky, 2015). distribution values (median .32) described facilitate utilization interpretation regressions models. We also provide specific, empirically grounded recommendations future research.