A Guide to Doing Statistics in Second Language Research Using SPSS and R

Larson‐Hall, Jenifer

doi:10.4324/9781315775661

Cited by 158 publications

(145 citation statements)

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“…Studies that examined whether power analyses were reported found that only a very small percentage of studies did so (2% in Plonsky & Gass, ; 1% in Plonsky, , and 7% in Ziegler, ). The proportion of studies that has reported checking statistical assumptions prior to employing inferential statistics is similarly small (3% in Plonsky & Gass, ; 17% in Plonsky, , and 36% in Ziegler, ), a result we find disturbing given the high co‐occurrence of parametric statistics on the one hand and non‐normal distributions, small samples, and outliers on the other (Larson‐Hall, ; Larson‐Hall & Herrington, ; Phakiti, ; Plonsky, ; Larson‐Hall, ; Plonsky et al., in press).…”

Section: Descriptive Statistics and Measures Of Study Qualitymentioning

confidence: 76%

Reporting and Interpreting Quantitative Research Findings: What Gets Reported and Recommendations for the Field

2015

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This paper presents a set of guidelines for reporting on five types of quantitative data issues: (1) Descriptive statistics, (2) Effect sizes and confidence intervals, (3) Instrument reliability, (4) Visual displays of data, and (5) Raw data. Our recommendations are derived mainly from various professional sources related to L2 research but motivated by results from investigations into how well the field as a whole is following these guidelines for best methodological practices, and illustrated by L2 examples. Although recent surveys of L2 reporting practices have found that more researchers are including important data such as effect sizes, confidence intervals, reliability coefficients, research questions, a priori alpha levels, graphics, and so forth in their research reports, we call for further improvement so that research findings may build upon each other and lend themselves to meta-analyses and a mindset that sees each research project in the context of a coherent whole.Keywords confidence intervals; effect sizes; language; L2; mean; meta-analysis; methodology; quantitative; raw data; reporting practices; standard deviation IntroductionThorough and consistent reporting practices are critical to advancing and informing second language (L2) theory and practice. In this chapter we call for quantitative L2 researchers to adopt a synthetic mindset-understanding that no research stands alone, that progress as a field happens best if we can pool research findings, and that reporting practices can either facilitate or impede Larson-Hall and PlonskyWhat Gets Reported and Recommendations for the Field this type of research. However, currently researchers have little in the way of L2-specific guidance or direction on what to present and how. As a baseline from which to assess L2 quantitative research, we will first introduce reporting practices based on recommendations from various sources related to L2 research. Next, we will review how well the field as a whole follows these guidelines by presenting results from secondary/meta-analytic research. We then propose a set of recommendations for improving the means by which quantitative L2 data are reported and interpreted. We do this for five main areas of quantitative reporting: (1) Descriptive statistics and other measures of study quality such as power, (2) Effect sizes and confidence intervals (CIs), (3) Instrument reliability, (4) Visual displays of data, and (5) Raw data.

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Section: Descriptive Statistics and Measures Of Study Qualitymentioning

confidence: 76%

Reporting and Interpreting Quantitative Research Findings: What Gets Reported and Recommendations for the Field

2015

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“…This scheme acted as the data collection instrument to help us understand how MRs were used and reported in L2 research articles. To the best of our knowledge, no previous coding scheme had been developed for examining practices related to MR. Consequently, we created the coding scheme for this study based on (a) the different checklists and recommendations in statistical guides (Field, ; Hair et al., ; Keith, ; Kelley & Maxwell, ; Larson–Hall, ; Meyers, Gamst, & Guarino, ; Pituch & Stevens, ; Plonsky, ; Plonsky & Oswald, ; Tabachnick & Fidell, ), (b) the recommendations in the publication manual of the American Psychological Association (APA, ), (c) suggestions, recommendations, and findings found in different recently published L2 research reviews (Larson–Hall & Plonsky, ; Plonsky, , , ), and (d) previous methodologically oriented syntheses (e.g., Lindstromberg, ; Marsden et al., ; Plonsky & Gonulal, ). As is typical in systematic reviews, the coding scheme underwent several rounds of development and piloting.…”

Section: Methodsmentioning

confidence: 99%

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

Plonsky

Ghanbar

2018

The Modern Language Journal

201

135

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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.

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“…To answer the research questions guiding the study, a series of Pearson product–moment correlation matrices were run among all learner ID subcomponents using the statistical software program SPSS (version 24.0). Bivariate correlations are interpreted based on statistical significance ( p ≤ 0.01**; p ≤ 0.05*) and their strength and robustness are based on their effect size (small ( r = .10), medium ( r = .30) or large ( r = .50) [Cohen, ]) and power level (see Larson–Hall, , pp. 104–111 for discussion of power levels and analysis).…”

Section: Methodsmentioning

confidence: 99%

Exploring the Dynamic Long‐Term Interaction Between Cognitive and Psychosocial Resources in Adult Second Language Development at Varying Proficiency

Serafini

2017

The Modern Language Journal

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This study draws on conceptual and methodological insights afforded within a dynamic systems perspective to explore shifting interrelationships between cognitive capacity and motivational resources in instructed adult second language (L2) learners of Spanish at increasing proficiency. Relationships that emerged showed both stability and fluctuation over a semester of instruction and varied by learners' stage of development. Findings support previous calls to improve upon mainstream approaches to conceptualizing and investigating learner individual differences (IDs) by adopting a holistic, non modular view of the L2 developmental system in general and learner IDs in particular (e.g., Dörnyei, , ; Dörnyei & Ryan, ; Larsen–Freeman, , , ). To further align with DST principles (see Hiver & Al‐Hoorie, ), future studies should endeavor to carry out longitudinal case studies with multiple data points in order to reveal intra‐individual complexity in the group‐level patterns seen here.

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A Guide to Doing Statistics in Second Language Research Using SPSS and R

Cited by 158 publications

References 0 publications

Reporting and Interpreting Quantitative Research Findings: What Gets Reported and Recommendations for the Field

Reporting and Interpreting Quantitative Research Findings: What Gets Reported and Recommendations for the Field

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

Exploring the Dynamic Long‐Term Interaction Between Cognitive and Psychosocial Resources in Adult Second Language Development at Varying Proficiency

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A Guide to Doing Statistics in Second Language Research Using SPSS and R

Cited by 158 publications

References 0 publications

Reporting and Interpreting Quantitative Research Findings: What Gets Reported and Recommendations for the Field

Reporting and Interpreting Quantitative Research Findings: What Gets Reported and Recommendations for the Field

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

Exploring the Dynamic Long‐Term Interaction Between Cognitive and Psychosocial Resources in Adult Second Language Development at Varying Proficiency

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