reproducer (version 0.5.2)

calcCliffdConfidenceIntervals: calcCliffdConfidenceIntervals

Description

This functions is a helper function. It assesses the significance one-sided and two-sided statistical of Cliff's d based on its confidence interval. The type of test is determined by the parameter One.Sided.Tests, the direction of one-sided tests is determined by the parameter Positive.MD.

Usage

calcCliffdConfidenceIntervals(
  d.value,
  d.variance,
  d.df,
  alpha = 0.05,
  alternative = "two.sided"
)

Value

The function returns a Boolean variable identifying whether the effect size is significant and the confidence interval bounds.

Arguments

d.value

This is the value of Cliff's d.

d.variance

This is the estimated variance of Cliff's d

d.df

The degrees of freedom.

alpha

This is the alpha level required for the statistical tests (default 0.05)

alternative

This defines whether a one-sided test or a two-sided (default) test is required. For a one-sided test use parameter values greater' or 'less' to define whether the d-value should be greater or less than zero.

Author

Barbara Kitchenham and Lech Madeyski

Examples

reproducer:::calcCliffdConfidenceIntervals(d.value=0.5, d.variance=0.04,d.df=18)
# A tibble: 1 x 5
#  d.tvalue d.pvalue d.ci.lower d.ci.upper d.sig
#                      
#1      2.5   0.0223     0.0479      0.782 TRUE

reproducer:::calcCliffdConfidenceIntervals(
  d.value=0.5,d.variance=0.04,d.df=18,alternative='greater')
# A tibble: 1 x 5
#  d.tvalue d.pvalue d.ci.lower d.ci.upper d.sig
#                    
#1    2.5   0.0112      0.123          1 TRUE

reproducer:::calcCliffdConfidenceIntervals(
  d.value=0.2,d.variance=0.04,d.df=18,alternative='greater')
# A tibble: 1 x 3
#  d.tvalue d.pvalue d.ci.lower d.ci.upper d.sig
#                      
#1        1    0.165     -0.133          1 FALSE

reproducer:::calcCliffdConfidenceIntervals(
  d.value=-0.5,d.variance=0.04,d.df=18,alternative='less')
# A tibble: 1 x 5
#  d.tvalue d.pvalue d.ci.lower d.ci.upper d.sig
#                    
#1     -2.5   0.0112         -1     -0.123 TRUE