Astrid Fritz
Biographic Data
| ID | 9294574 |
|---|---|
| NAME | Astrid Fritz |
| GIVEN NAMES | Astrid |
| FAMILY NAME | Fritz |
| SIGNATURE | FRITZ A |
| AFFILIATIONS | University of Salzburg |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2014 |
| H-INDEX | 0 |
Publication Bias in Psychology
BACKGROUND: The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias. METHODS: We investigate whether effect size is independent from sample size in psych…
On the correlation between effect size and sample size
In a comment on our paper, Bradley and Brand (2013) argue that effect sizes are exaggerated owing to low power and publication bias. They propose to correct these exaggerations by application of a specific formula leading to a better estimate of the “true” effect size. In a simulation we test the effect of this formula and find this “corrective” approach unsatisfactory. We agree with Bradley and Brand on the points that effect sizes are important…
A comprehensive review of reporting practices in psychological journals
Over-reliance on significance testing has been heavily criticized in psychology. Therefore the American Psychological Association recommended supplementing the p value with additional elements such as effect sizes, confidence intervals, and considering statistical power seriously. This article elaborates the conclusions that can be drawn when these measures accompany the p value. An analysis of over 30 summary papers (including over 6,000 article…
No prominent works on this page.
On the correlation between effect size and sample size
In a comment on our paper, Bradley and Brand (2013) argue that effect sizes are exaggerated owing to low power and publication bias. They propose to correct these exaggerations by application of a specific formula leading to a better estimate of the “true” effect size. In a simulation we test the effect of this formula and find this “corrective” approach unsatisfactory. We agree with Bradley and Brand on the points that effect sizes are important…
A comprehensive review of reporting practices in psychological journals
Over-reliance on significance testing has been heavily criticized in psychology. Therefore the American Psychological Association recommended supplementing the p value with additional elements such as effect sizes, confidence intervals, and considering statistical power seriously. This article elaborates the conclusions that can be drawn when these measures accompany the p value. An analysis of over 30 summary papers (including over 6,000 article…
Publication Bias in Psychology
BACKGROUND: The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias. METHODS: We investigate whether effect size is independent from sample size in psych…
Mathematics (3 works) · Meta-analysis and systematic reviews (3 works) · Psychology (3 works) · Statistics (3 works) · Confidence interval (2 works) · Correlation (2 works) · Econometrics (2 works) · Medicine (2 works) · Meta-analysis (2 works) · Psychometric Methodologies and Testing (2 works)