reproducer (version 0.5.2)

calculateLargeSampleRandomizedDesignEffectSizes: calculateLargeSampleRandomizedDesignEffectSizes

Description

The function uses a simulates a large experiment to estimate the asymptotic values of the probability of superiority, Cliff's d and the standardized mean difference data for a two group randomized experiment for four different distributions: Normal (i.e. type='n'), log-normal (i.e. type='l'), gama (i.e. tyep='g') and Laplace (i.e., type='lap').

Usage

calculateLargeSampleRandomizedDesignEffectSizes(
  meanC = 0,
  sdC = 1,
  diff = 0,
  N = 5e+06,
  type = "n",
  StdAdj = 0
)

Value

A tibble identifying the sample statistics and the values of the probability of superiority, Cliff's d and StdMD (labelled StdES)

Arguments

meanC

to act as the mean of the distribution (default 0) used to generate the control group data (note for the gamma distribution this is the rate parameter and must not be zero)

sdC

the variance/spread of the distribution (default 1) used to generate the control group data.

diff

a value (default 0) added to meanC to generate the treatment group data.

N

the size of each group (default 5000000)

type

the distribution of the data to be generated (default 'n')

StdAdj

a value (default 0) that can be added to sdC to introduce heterogeneity into the tretament group

Author

Barbara Kitchenham and Lech Madeyski

Examples

set.seed=400
calculateLargeSampleRandomizedDesignEffectSizes(
  meanC=0, sdC=1, diff=.5, N=100000, type='n',StdAdj = 0)
# A tibble: 1 x 9
#  MeanC   SdC MeanT   SdT  Phat Cliffd   UES   Var StdES
#           
#1     0     1   0.5     1 0.637  0.275 0.499  1.01 0.497