Multiple Regression in L2 Research: A Methodological Synthesis and Guide to InterpretingR2Values

By Luke Plonsky, H. Ghanbar. The Modern Language Journal, 2018

313 citations recorded by the source corpus.

Multiple regression is a family of statistics used to investigate the relationship between a set of predictors and a criterion (dependent) variable. This procedure is applicable in a variety of research contexts and data structures. Consequently, and similar to quantitative traditions in sister‐disciplines such as education and psychology (see Skidmore & Thompson, 2010), second language researchers have turned increasingly to multiple regression. The present study employs research synthetic techniques to describe and evaluate the use of this procedure in the field. Five hundred and forty‐one regression analyses (K = 171) were coded for different models, variables, procedures, reporting practices, and overall variance explained (R2). Summary results reveal a number of inconsistencies (e.g., model types) as well as a lack of transparency (e.g., missing/unreported reliability estimates; see Larson–Hall & Plonsky, 2015). The distribution of R2 values (median =.32) is described to facilitate utilization and interpretation of regressions models. We also provide specific, empirically grounded recommendations for future research. [ABSTRACT FROM AUTHOR]

Subfields: Computer Networks and Communications, Food Science, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/e6e3b442e786e14bc533bf96a0209f1a890266c5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Judit Kormos
2. Shungo Suzuki
3. Luke Plonsky

In Food Science

1. Judit Kormos
2. Shungo Suzuki
3. Luke Plonsky

In Management Science and Operations Research

1. Jean–Marc Dewaele
2. Y. Teimouri
3. Judit Kormos
4. E. Marsden
5. Kazuya Saito
6. Shungo Suzuki
7. Julia Goetze
8. Farhad Tabandeh

Citations in the corpus

• The Effect of Perception of Teacher Characteristics on Spanish EFL Learners’ Anxiety and Enjoyment (2019, background): “The effect size could be described as small (Plonsky & Ghanbar, 2018).”
• L2 grit: Passion and perseverance for second-language learning (2020, background): “the overall model were quite small (Cohen, 1988; Plonsky & Ghanbar, 2018).”
• LINGUISTIC DIMENSIONS OF COMPREHENSIBILITY AND PERCEIVED FLUENCY: AN INVESTIGATION OF COMPLEXITY, ACCURACY, AND FLUENCY IN SECOND LANGUAGE ARGUMENTATIVE SPEECH (2019, methodology): “The assumptions of multiple regression were checked in terms of normality, outliers, the independence of error terms (the Durbin-Watson tests) and multicollinearity among predictor variables (variance inflation rate [VIF]), following Plonsky and Ghanbar (2018).”
• A methodological synthesis and meta-analysis of judgment tasks in second language research (2020, background): “…research (Marsden et al., 2018a); quantitative analyses and reporting practices (Plonsky, 2013, 2014); study designs (Marsden and Torgerson, 2012; Plonsky and Gonulal, 2015); multiple regression (Plonsky and Ghanbar, 2018; Plonsky and Oswald, 2017); and structural equation modeling (Winke, 2014).”
• SECOND LANGUAGE ANXIETY AND ACHIEVEMENT (2019, background): “First, some of the variance explained by these individual differences is likely shared, leading to a somewhat inflated overall value (see Plonsky & Ghanbar, 2018; Plonsky & Oswald, 2017, for discussions on shared variance among predictors).”