mbir (version 1.3.5)

smd_test: Standardized Mean Difference Test

Description

Performs two-sample difference of means analysis to produce magnitude-based inferences. Evaluates both normality and homogeneity, performs either t-test or wilcoxon test, computes effect sizes and estimates magnitude-based inferences. Allows both independent and paired designs.

Usage

smd_test(x, y, paired = c(TRUE, FALSE), auto = TRUE, var = TRUE,
  normal = TRUE, conf.int = 0.9, mu = 0, swc = 0.5, plot = FALSE)

Arguments

x, y

numeric vectors of data values

paired

(character) logical indicator specifying if x and y are paired (TRUE) or independent (FALSE)

auto

(character) logical indicator specifying if user wants function to programmatically detect statistical procedures. Defaults to TRUE

var

(optional) if auto = F, logical indicator specifying if homogeneity of variance assumed. Defaults to TRUE

normal

(optional) if auto = F, logical indicator specifying if normality assumed. Defaults to TRUE

conf.int

(optional) confidence level of the interval. Defaults to 0.90

mu

(optional) number indicating true difference in means to test against. Defaults to zero.

swc

(optional) number indicating smallest worthwhile change. Defaults to 0.5

plot

(optional) logical indicator specifying to print associated plot. Defaults to FALSE

Value

Associated effect size measures (d, r, odds ratio) and respective confidence intervals based upon which statistical test(s) performed.

Details

Refer to vignette for further information.

Examples

# NOT RUN {
a <- rnorm(25, 80, 35)
b <- rnorm(25, 100, 50)

smd_test(a, b, paired = FALSE, conf.int=0.95)
# }