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
  • t-values Calculator
  • p-values Calculator

• 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

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