| RandomExperimentSimulations {reproducer} | R Documentation |
RandomExperimentSimulations
Description
This function performs multiple simulations of two-group balanced experiments for one of four distributions and a specific group size. It identifies the average value of phat, Cliff' d and their variances. It either returns the effect sizes for each non-parametric effect size or it reports the number of times the each non-parametric effect size is assessed to be significantly different from zero. We also present the values for the t-test as a comparison. For log-normal data the results of analysing the transformed data are also reported.
Usage
RandomExperimentSimulations(
mean,
sd,
diff,
N,
reps,
type = "n",
seed = 123,
StdAdj = 0,
alpha = 0.05,
returnData = FALSE,
AlwaysTwoSidedTests = FALSE
)
Arguments
mean |
The default mean used for both groups (one treatment group and one control group). It can be changed for the treatment group using the parameter diff |
sd |
This is the default spread for both groups. It must be a real value greater than 0. It can be adjusted for the treatment group using the parameter StdAdj |
diff |
This is added to the treatment group mean. It can be a real value avd can take the value zero. |
N |
this is the number of observations in each group. It must be an integer greater than 3. |
reps |
this identifies the number of times each experiment simulation is replicated. |
type |
this specifies the underlying distribution used to generate the data. It takes the values 'n' for a normal distribution, 'l' for lognormal distribution,'g' for a gamma distribution, 'lap' for a Laplace distribution. |
seed |
This specifies the initial seed for the set of replications (default 123). |
StdAdj |
this specifies the extent of variance instability introduced by the treatment and it must be non-negative but can be 0. |
alpha |
This specifies the level of significance used for statistical tests (default 0.05). |
returnData |
If TRUE, the function returns the individual effect sizes and their variances, otherwise it returns summary statistics (default FALSE). |
AlwaysTwoSidedTests |
If set to FALSE (default) the algorithms uses one-sided tests if diff!=0 and two-sided tests if diff=0. If set to TRUE the algorithm always uses two-sided tests. |
Author(s)
Barbara Kitchenham and Lech Madeyski
Examples
as.data.frame(
RandomExperimentSimulations(
mean = 0, sd = 1, diff = 0.5, N = 20, reps = 50, type = "n",
seed = 123, StdAdj = 0, alpha = 0.05))
# phat phatvar sigphat emp.phat.var d dvar sigd
# 1 0.636675 0.007980072 0.38 0.006413391 0.27335 0.03257962 0.36
# emp.d.var tpower ES Variance StdES MedDiff
#1 0.02565356 0.41 0.4849609 0.988889 0.4982554 0.4666802
#as.data.frame(
# RandomExperimentSimulations(
# mean = 0, sd = 1, diff = 0.5, N = 20, reps = 500, type = "n",
# seed = 123, StdAdj = 0, alpha = 0.05))
# phat phatvar sigphat emp.phat.var d dvar sigd emp.d.var
# 1 0.63915 0.007925803 0.444 0.007904962 0.2783 0.03235111 0.414 0.03161985
# tpower ES Variance
# 1 0.444 0.4999034 1.002012
# 1 StdES MedDiff
# 1 0.5099792 0.4901394
#as.data.frame(
# RandomExperimentSimulations(
# mean = 0, sd = 1, diff = 0.2, N = 20, reps = 500, type = "n",
# seed = 123, StdAdj = 0, alpha = 0.05, AlwaysTwoSidedTests = TRUE))
# phat phatvar sigphat emp.phat.var d dvar sigd emp.d.var
# 1 0.55762 0.008596555 0.092 0.008457325 0.11524 0.03505528 0.076 0.0338293
# tpower ES Variance StdES MedDiff
# 1 0.1 0.1999034 1.002012 0.2043908 0.1901394
#as.data.frame(
# RandomExperimentSimulations(
# mean = 0, sd = 1, diff = 0.2, N = 20, reps = 500, type = "n",
# seed = 123, StdAdj = 0, alpha = 0.05, AlwaysTwoSidedTests = FALSE))
# phat phatvar sigphat emp.phat.var d dvar sigd emp.d.var
# 1 0.55762 0.008596555 0.154 0.008457325 0.11524 0.03505528 0.146 0.0338293
# tpower ES Variance
# 1 0.16 0.1999034 1.002012
# StdES MedDiff
# 1 0.2043908 0.1901394
RandomExperimentSimulations(
mean = 0, sd = 1, diff = 0.5, N = 20, reps = 10, type = "l", seed = 456,
StdAdj = 0, alpha = 0.05, returnData = TRUE, AlwaysTwoSidedTests = FALSE)
# A tibble: 10 x 6
# Cliffd CliffdSig PHat PHatSig StdES ESSig
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 -0.185 0 0.407 0 -0.246 0
# 2 -0.08 0 0.46 0 0.185 0
# 3 0.1 0 0.55 0 0.149 0
# 4 0.42 1 0.71 1 0.885 1
# 5 0.51 1 0.755 1 0.827 1
# 6 0.185 0 0.592 0 0.628 1
# 7 0.465 1 0.732 1 0.818 1
# 8 0.42 1 0.71 1 0.341 0
# 9 0.37 1 0.685 1 0.419 0
# 10 0.115 0 0.557 0 0.273 0