What Future Quantitative Social Science Research Could Look Like: Confidence Intervals for Effect Sizes

By B. Thompson. 2002

536 citations recorded by the source corpus.

Subfields: General Health Professions, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fdc6d9fb23dff14afac91df1ea4cf8f7469c5d51

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In General Health Professions

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Considerations in determining sample size for pilot studies. (2008, background): “Calculation of confidence intervals for effect sizes, although recommended (Thompson, 2002), involves use of noncentral distributions (Cumming & Finch, 2001) and is not implemented in most widely available statistical packages.”
The Effects of Acceleration on High-Ability Learners: A Meta-Analysis (2011, methodology): “A “meta-analytic thinking” approach was adopted for interpreting the results in this meta-analysis (cf., Cumming & Finch, 2001; Thompson, 2002).”
Why P Values Are Not a Useful Measure of Evidence in Statistical Significance Testing (2008, methodology): “Substantially overlapping CIs suggest tenable estimates of the same population parameter, and we applaud the very useful recent work in this area (e.g., Cumming & Finch, 2001, 2005; Fidler, Thomason, Cumming, Finch, & Leeman, 2005; Goldstein & Healy, 1995; Schenker & Gentleman, 2001; Schmidt, 1996; ”
Mindfulness and acceptance approaches to sporting performance enhancement: a systematic review (2017, methodology): “We extracted effect sizes with confidence intervals (CIs) INTERNATIONAL REVIEW OF SPORT AND EXERCISE PSYCHOLOGY 143 when reported on primary outcomes, because they allow for more useful comparisons across studies (B. Thompson, 2002), and significance test where CIs were not available.”
Essentials of Psychological Testing (2005, background): “An excellent collection of readings on reliability, with more detailed and extensive explanations of many topics covered in this chapter, can be found in Score Reliability: Contemporary Thinking on Reliability Issues, edited by Bruce Thompson (2003b). Rapid Reference 4.”
EFL classroom peer assessment: Training effects on rating and commenting (2008, background): “Due to such limited and diverse findings, a quantitative summary of available studies invoking prior effect sizes may situate the present study in the proper context of related research, as recommended by researchers such as Thompson (2002).”
Confidence Intervals for Effect Sizes: Applying Bootstrap Resampling. (2016, background): “The utility of ES, CI, and CIES was first recognized on an international level by the 1999 APA Task Force on Statistical Inference report (Wilkinson, 1999). The Task Force developed a list of best practices to modernize statistical practice for the 21st century. These best practices discouraged over”
Alternatives to P value: confidence interval and effect size (2016, background): “The main concept of BESD is that “r” is the representative value of the difference between two groups when grouping variables are converted into one dichotomy and observed values into another, such as being above or below a specific value like a mean [12-14].”
A Reliability Induction and Reliability Generalization Study of the Cage Questionnaire (2004, background): “Although failure to report score reliability and other important psychometric information (e.g., effect sizes) inhibits scientific progress generally (Thompson, 1994, 2002), its effects are also quite local.”
Effect-Size Measures and Meta-Analytic Thinking in Counseling Psychology Research (2006, methodology): “Thompson (2002) argued that using CIs around effect sizes can facilitate meta-analytic thinking and can advance scientific inquiry.”
Book Review: Beyond Significance Testing: Reforming Data Analysis Methods in Behavioral Research (2006, unknown): “More work is also needed regarding the linkage between measurement and effect size estimation (cf. Henson, 2001; Henson & Thompson, 2002).”
Computation of measures of effect size for neuroscience data sets (2011, methodology): “The true merit of CIs, however, is that they facilitate a comparison of effects across studies, by deﬁning a range of expected values of effects independent of any null hypothesis (Thompson, 2002; Nakagawa & Hauber, 2011).”
The Improvement Rate Difference for Single-Case Research (2009, background): “Practical significance is achieved when behavior change has a practical impact on the client’s daily life (Shaver, 1991; Thompson, 2002b), and the more demanding clinical significance is change from a dysfunctional to functional range of activity (Jacobson, Follette, & Revenstorf, 1984).”
Design‐based science and student learning (2004, methodology): “To determine the degree to which the results diverged from the null hypothesis (Thompson, 2002), an effect size using the posttest mean, the pretest mean, and the pretest standard deviation (SD) were calculated for each pre-/posttest pair.”
A meta-analysis of the effectiveness of intelligent tutoring systems on college students' academic learning (2014, unknown): “Instead, we adopted a meta-analytic thinking approach for interpreting the results (cf. Cumming & Finch, 2001; Thompson, 2002, 2006).”