1996
DOI: 10.1177/0013164496056005002
|View full text |Cite
|
Sign up to set email alerts
|

Practical Significance: A Concept Whose Time Has Come

Abstract: Statistical significance is concerned with whether a research result is due to chance or sampling variability; practical significance is concerned with whether the result is useful in the real world. A growing awareness of the limitations of null hypothesis significance tests has led to a search for ways to supplement these procedures. A variety of supplementary measures of effect magnitude have been proposed. The use of these procedures in four APA journals is examined, and an approach to assessing the practi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

25
1,222
2
60

Year Published

1998
1998
2015
2015

Publication Types

Select...
7
2

Relationship

0
9

Authors

Journals

citations
Cited by 1,456 publications
(1,338 citation statements)
references
References 38 publications
25
1,222
2
60
Order By: Relevance
“…Modelling heterogeneous residual variance by country at level 1 of the model for teaching resources corrected this and achieved a better model fit (Garson, 2013). (Kirk, 1996) ( Thompson, 2006) List of Tables Table 1: Demographic characteristics of samples in Australia and Malta Effect sizes (partial) r (calculated from t): approximate guidelines: small = r > 0.1; medium = r > 0.24; large = r > 0.37 (Kirk, 1996;Thompson, 2006) …”
Section: Appendix A: Principal Components Analysismentioning
confidence: 99%
“…Modelling heterogeneous residual variance by country at level 1 of the model for teaching resources corrected this and achieved a better model fit (Garson, 2013). (Kirk, 1996) ( Thompson, 2006) List of Tables Table 1: Demographic characteristics of samples in Australia and Malta Effect sizes (partial) r (calculated from t): approximate guidelines: small = r > 0.1; medium = r > 0.24; large = r > 0.37 (Kirk, 1996;Thompson, 2006) …”
Section: Appendix A: Principal Components Analysismentioning
confidence: 99%
“…Small differences can be statistically ''significant'' simply because of a large sample size. This has prompted some to argue that tests of statistical significance are not generally useful (Carver, 1978(Carver, , 1993Cohen, 1994;Hunter, 1997;Kirk, 1996;Schmidt, 1992). Rather, these critics of significance testing argue that confidence intervals and measures of effect size should be the focal point of research findings.…”
mentioning
confidence: 99%
“…We obtained a between-school standard deviation, 3.913, from the unconditional ANOVA model (not shown in the table). Plugging two measures into a commonly used effect size formula (to calculate standardized mean differences) (see Borg and Gall, 1989;Hopkins, Hopkins, and Glass, 1996;Kim, 1995;Kirk, 1996), we found a difference of 0.20 standard deviations (from -0.767/3.913) in students' reading scores between Catholic and non-Catholic private school sectors. In other words, non-Catholic private school students were estimated to score 0.20 standard deviations higher (or an 8 percentile difference) in their reading achievement test, on average, than Catholic school students.…”
Section: Results and Interpretations: Examining The Effectiveness Ofmentioning
confidence: 92%