cliff: Compute Effect Size

In mbRes: Exploration of Multiple Biomarker Responses using Effect Size

Compute Effect Size

Description

cliff calculates Cliff's delta statistic using the rank sum method.

Usage

cliff(v1, v0)

Arguments

v1	a vector, biomarker values from the treatment group.
v0	a vector, biomarker values from the control group.

Value

cliff returns a numeric that is the Cliff's delta of the treatment group.

References

Cliff, N. (1993). Dominance statistics: Ordinal analyses to answer ordinal questions. Psychological Bulletin, 114(3), 494–509. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/0033-2909.114.3.494")}.

Vargha, A., & Delaney, H. D. (2000). A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong. Journal of Educational and Behavioral Statistics, 25(2), 101–132. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3102/10769986025002101")}.

Ruscio, J., & Mullen, T. (2012). Confidence Intervals for the Probability of Superiority Effect Size Measure and the Area Under a Receiver Operating Characteristic Curve. Multivariate Behavioral Research, 47(2), 201–223. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00273171.2012.658329")}.

See Also

CalcA1.

Examples

set.seed(1)
setting <- setpop()
temp <- simul(setting$pop_mean)
cliff(subset(temp$sam, Site == "S1", Bmk1, drop = TRUE),
subset(temp$sam, Site == "S0", Bmk1, drop = TRUE))

mbRes documentation built on March 31, 2023, 8:14 p.m.