ind.twoway.second: A two-way design with independent samples using published... In rpsychi: Statistics for psychiatric research

Description

ind.twoway.second conducts a two-way design with independent samples, namely two-way randomized-group analysis of variance, using published work.

Usage

 1 2 ind.twoway.second(m, sd, n, unbiased = TRUE, sig.level = 0.05, digits = 3)

Arguments

 m a matrix contains the means sd a matrix contains the sample/unbiased standard deviations n a matrix contains the sample size unbiased sd contains unbiased standard deviations (unbiased = TRUE, default) or sample standard deviations (unbiased = FALSE) sig.level a numeric contains the significance level (default 0.05) digits the specified number of decimal places (default 3)

Details

This function conducts a two-way design with independent samples, namely two-way randomized-group analysis of variance, using published work. Statistical power is calculated using the following specifications:

(a) small (η^2 = 0.01), medium (η^2 = 0.06), and large (η^2 = 0.14) population effect sizes, according to the interpretive guideline for effect sizes by Cohen (1992)

(b) sample size specified by n

(c) significance level specified by sig.level

Value

The returned object of ind.oneway.second contains the following components:

 anova.table returns a ANOVA table containing sums of squares, degrees of freedom, mean squares, F values omnibus.es returns a omnibus effect sizes which is a partial η^2, and its' confidence interval for each main and interaction effect power returns statistical power for detecting small (η^2 = 0.01), medium (η^2 = 0.06), and large (η^2 = 0.14) population effect sizes

Author(s)

Yasuyuki Okumura
Department of Social Psychiatry,
National Institute of Mental Health,
National Center of Neurology and Psychiatry
yokumura@blue.zero.jp

References

Cohen B (2000) Calculating a factorial ANOVA from means and standard deviations. Understanding Statistics, 1, 191-203.

Cohen J (1992) A power primer. Psychological Bulletin, 112, 155-159.

Kline RB (2004) Beyond significance testing: Reforming data analysis methods in behavioral research. Washington: American Psychological Association.

Tabachnick BG, Fidell LS (2007) Experimental designs using ANOVA. Belmont, CA: Thomson.