aipe.smd {MBESS}R Documentation

Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized mean difference

Description

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.

Usage

ss.aipe.smd.full(delta, conf.level, width, ...)
ss.aipe.smd.lower(delta, conf.level, width, ...)
ss.aipe.smd.upper(delta, conf.level, width, ...)

Arguments

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

Value

n The necessary sample size per group in order to achieve the desired degree of precision.

Warning

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.

Note

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.

Author(s)

Ken Kelley (Indiana University; KKIII@Indiana.Edu)

References

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.

See Also

'ss.aipe.smd'


[Package MBESS version 0.0.7 Index]