"Statistical," "practical", and "clinical": How many kinds of significance do counselors need to consider?

By B. Thompson. 2002

417 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Social Psychology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/69b8cf3d735cb56254976860e1684d72472e33db

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In Management Science and Operations Research

In Social Psychology

In Statistics and Probability

Citations in the corpus

Statistical Significance, Effect Size Reporting, and Confidence Intervals: Best Reporting Strategies. (2004, background): “Accessible summaries of the related issues and choices have been provided by several researchers (cf. Olejnik & Algina, 2000; Thompson, 2002).”
Do Differing Types of Field Experiences Make a Difference in Teacher Candidates' Perceived Level of Competence? (2010, methodology): “Because all analyses are correlational and attenuated by reliability, it is important to examine the obtained reliability (Thompson, 2002, 2003).”
The Threat of Common Method Variance Bias to Theory Building (2010, background): “…include effect sizes and confidence intervals (Callahan & Reio, 2006), statistical power (Cohen, 1988), statistical and practical significance (Thompson, 2002), nonresponse bias (Bartlett, Bartlett, & Reio, 2008; Rogelberg & Luong, 1998), Type I and Type II error (Williams & Brown, 1994), and…”
An effect size primer: A guide for clinicians and researchers. (2009, background): “As noted by numerous scholars (e.g., Cohen, 1992; Snyder & Lawson, 1993; Thompson, 2002), rigid adherence to arbitrary guidelines is not recommended.”
Enhancing the Interpretation of Significant Findings: The Role of Mixed Methods Research (2004, background): “Moreover, an effect size index provides information about the theoretical or applied significance of a result (Thompson, 2002; Vacha-Haase, 2001; Vaske, Gliner, & Morgan, 2002).”
Cultural Context of Career Choice: Meta-Analysis of Race/Ethnicity Differences. (2005, background): “Effect sizes are also an indication of practical significance (Thompson, 2002).”
Charity Brand Personality: The Relationship With Giving Behavior (2008, background): “As Thompson (2002) noted, testing for statistical significance does not clearly indicate whether the results are “important,” and in the present case, relatively minor differences in mean scores may be statistically significant yet represent little practical difference in terms of perception…”
You Think You’ve Got Trivials? (2003, background): “Their point is well taken, despite the apparent recanting of this form of persuasion by Thompson (2002), who cautioned “headcounts of views are not perfect indicators of truth” (p. 85).”
What Future Quantitative Social Science Research Could Look Like: Confidence Intervals for Effect Sizes (2002, background): “EDUCATIONAL RESEARCHER 30 or vice versa, his tentative benchmarks potentially have wide applicability (Kirk, 1996; Thompson, 2002).”
Evaluating Evidence for Conceptually Related Constructs Using Bivariate Correlations (2017, background): “Researchers should also consider the context of their study, as effect size can be influenced by various factors (e.g., sample size, normality, and scale type; see Thompson, 2002, and Sink & Stroh, 2006, for a detailed discussion on effect sizes).”
Effect size, confidence interval and statistical significance: a practical guide for biologists (2007, background): “This is because the construction of CIs around effect size involves the use of non-central t and F distributions, which most biologists have never heard of and for which no generic formulae exist (Thompson, 2002a).”
The Fifth edition of the Apa Publication Manual: Why its Statistics Recommendations are so Controversial (2002, background): “Thompson (2002b) detailedwhat the recommended and the not recommended uses of CIs are, including CIs for effect sizes.”
Alternatives to P value: confidence interval and effect size (2016, background): “These biases are more significant when the sample size is small, the number of measured variables is large, and the population effect size is small [12].”