calculateLargeSampleRandomizedDesignEffectSizes function
calculateLargeSampleRandomizedDesignEffectSizes
calculateLargeSampleRandomizedDesignEffectSizes
The function 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").
calculateLargeSampleRandomizedDesignEffectSizes( meanC =0, sdC =1, diff =0, N =5e+06, type ="n", StdAdj =0, reporttrans ="No")
Arguments
meanC: to act as the mean of the distribution used to generate the control group data (default 0) (note for the gamma distribution this is the rate parameter and must not be zero)
sdC: the variance/spread of the distribution used to generate the control group data (default 1).
diff: a value added to meanC to generate the treatment group data (default 0).
N: the size of each group (default 5000000)
type: the distribution of the data to be generated (default "n").
StdAdj: a value that can be added to sdC to introduce heterogeneity into the treatment group (default 0).
reporttrans: If set to "Yes" AND type="l" the algorithm returns the values obtained by analysing applying the logarithmic transformation to the simulated data (default "No").
Returns
A tibble identifying the sample statistics and the values of the probability of superiority, Cliff's d and StdMD (labelled StdES)