t, p, & Effect Size Estimator
t, p, & Effect Size Estimator
Estimate t from p and vice versa, including associated effect sizes.
Instructions
- This tool estimates t-scores from p-values and vice versa for a given number of degrees of freedom υ.
- Just enter a (t,υ) or (p,υ) pair and this tool will solve for the missing term.
- The tool also estimates the effect sizes associated to the (t,p,υ) triplet.
What is computed?
- This tool computes t-scores from p-values and vice versa. These conversions are the same as those obtained from our
- The tool also estimates the statistics that one would obtain if the computed estimates correspond to a set of paired variables (x, y), or to effect sizes from any two samples of same sizes (n1 and n2); i.e. samples with same degrees of freedom (υ1 and υ2).
- The following are estimated
- Pearson's Correlation Coefficient,
- Standard Error of Correlations,
- Signal (explained variations) or r2,
- Noise (unexplained variations) or 1 - r2,
- Signal-to-Noise Ratio or Cohen's f2,
- Square Root of Signal/Noise Ratio or Cohen's f,
- Omega Squared,
- Standardized Mean Difference or Cohen's d,
- Hedges's g,
- Log Odds Ratio L,
Although SE and N are not effect sizes, these are listed as supporting data. Conversions between effect sizes are available online (Beasley, 2007; Borenstein, Hedges, Higgins, & Rothstein, 2009; Psychometrica.de, 2017; Rosenthal & Rubin, 1982).
Who can use this tool?
- Anyone that need to do t, p and effect sizes testing.
Suggested Exercises
- Show that for any two samples of equal sizes
.
- Show that a log odds ratio L is about 3.6 times Cohen's f; i.e.,
L = (3.62759...)f.
- What is the statistical meaning of the following statements?
- Cohen's d is twice Cohen's f; i.e. d = 2f.
- d is the derivative of S/N = f2 respect to t.
- 1/N is found in the PDF expression of Student's t Distribution.
References
- Beasley, M. (2007).Conversion of Common Test Statistics to r and d Values Retrieved from UAB.edu site.
- Borenstein, M., Larry V. Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009).
Converting Among Effect Sizes. Introduction to Meta-Analysis. Chapter 7. Wiley Online Library.
- Pyschometrica.de (2017). Computation of Effect Sizes.
- Rosenthal, R., & Rubin, D. B. (1982). A Simple, General Purpose Display of Magnitude of Experimental Effect. Journal of Educational Psychology, Vol 74, 2, 166-169. American Psychological Association.
Feedback
Contact us for any suggestion or question regarding this tool.
