aipe.smd {MBESS} | R Documentation |
A set of functions that ss.aipe.smd
calls upon to calculate the appropriate sample size
for the standardized mean difference such that the expected value of the confidence interval
is sufficiently narrow.
ss.aipe.smd.full(delta, conf.level, width, ...) ss.aipe.smd.lower(delta, conf.level, width, ...) ss.aipe.smd.upper(delta, conf.level, width, ...)
delta |
the population value of the standardized mean difference |
conf.level |
the desired degree of confidence (i.e., 1-Type I error rate) |
width |
desired width of the specified (i.e., Lower , Upper , Full ) region of the confidence interval |
... |
specify additional parameters in functions these functions call upon |
n |
The necessary sample size per group in order to achieve the desired degree of precision. |
The returned value is the sample size per group. Currently only
ss.aipe.smd.full
returns the exact value. However, ss.aipe.smd.lower
and ss.aipe.smd.upper
are nearly exact and provide very close estimates to the true sample size necessary.
The function ss.aipe.smd
is the function users should generally use. The function ss.aipe.smd
calls upon
these functions as needed. They can be thought of loosely as internal MBESS functions.
Ken Kelley (Indiana University; KKIII@Indiana.Edu)
Cohen, J. (1988) Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
Cumming, G. & Finch, S. (2001) A primer on the understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions, Educational and Psychological Measurement, 61, 532–574.
Hedges, L. V. (1981). Distribution theory for Glass's Estimator of effect size and related estimators. Journal of Educational Statistics, 2, 107–128.
Kelley, K., Maxwell, S. E., & Rausch, J. R. (2003) Obtaining Power or Obtaining Precision: Delineating Methods of Sample-Size Planning, Evaluation and the Health Professions, 26, 258–287.
Kelley, K. (2005) The effects of nonnormal distributions on confidence intervals around the standardized mean difference: Bootstrap and parametric confidence intervals, Educational and Psychological Measurement, 65, 51–69.
Steiger, J. H., & Fouladi, R. T. (1997) Noncentrality interval estimation and the evaluation of statistical methods. In L. L. Harlow, S. A. Mulaik,&J.H. Steiger (Eds.), What if there where no significance tests? (pp. 221-257). Mahwah, NJ: Lawrence Erlbaum.
'ss.aipe.smd'