Approximate Confidence Interval for Effect Size Base on Bootstrap Resampling Method

This paper presents the confidence intervals for the
effect size base on bootstrap resampling method. The meta-analytic
confidence interval for effect size is proposed that are easy to
compute. A Monte Carlo simulation study was conducted to compare
the performance of the proposed confidence intervals with the
existing confidence intervals. The best confidence interval method
will have a coverage probability close to 0.95. Simulation results
have shown that our proposed confidence intervals perform well in
terms of coverage probability and expected length.

Authors:

• S. Phanyaem

Keywords:

• Effect size
• confidence interval
• Bootstrap Method.

References:

[1] G. V. Glass, “Primary secondary and meta-analysis of research,”
Educational Researcher, 1976, pp. 3-5.
[2] L. V. Hedges, “Fixed and random effects models in meta-analysis,”
Psychological Methods, vol. 3, 1998, pp. 486-504.
[3] C. F. Bond, W.L. Wiitala and F. D. Richard, “Meta-analysis of raw
mean differences,” Psychological Methods, vol. 8, 2003, pp. 406-418.
[4] D.G. Bonett, “Confidence intervals for standardized linear contrasts of
means,” Psychological Methods, vol. 13, 2008a, pp. 99-109.
[5] D. G. Bonett, “Meta-analytic interval estimation for standardized and
unstandardized mean differences,” Psychological Methods, vol. 14 2009,
pp. 225-238.
[6] B. Efron and R. Tibshirani, “Bootstrap methods for standard errors,
confidence intervals and other measure of statistical accuracy,”
Statistical Science, vol. 1, 1986, 54-57.
[7] J. Cohen, Statistical power analysis for the behavioral sciences (2nd ed.).
Hillsdale, NJ: Erlbaum.