| calculateNullESAccuracy {reproducer} | R Documentation |
calculateNullESAccuracy
Description
The function uses simulation to assess the accuracy when the mean difference is zero, and the type 1 error rates of parametric and non-parametric effect sizes for both two group randomized designs and four group randomized block designs, for each of four different distributions.
Usage
calculateNullESAccuracy(
mean = 0,
sd = 1,
N = 10,
reps = 10,
type = "n",
seed = 123,
StdAdj = 0,
Blockmean = 0.5
)
Arguments
mean |
The mean of the baseline distribution. |
sd |
The standard deviation or shape of the baseline distribution |
N |
The number of observations per group for two group experiments and N/2 the sample sizes for four group experiments. N must be even to ensure equal N/2 defines appropriate sample sizes per group for 4 group experiments |
reps |
The number of replications (i.e. two-group and four group experiments) to be simulated |
type |
A string parameter defining the distribution being simulated i.e. 'n' for normal data, 'l' for log-normal data, 'g' for gamma data and 'lap' for LaPlace data. |
seed |
A starting value for the simulations |
StdAdj |
A numerical parameter that can be used to add additional variance for normal, lognormal and Laplce data and to change the shape parameter for gamma data. |
Blockmean |
A numerical parameter used to introduce a fixed Block effect for four group experiments |
Value
A tibble identifying the median absolute error for the effect sizes Cliff's d, phat and StdMD and the Type 1 error rate, estimated from the proportion of significant effect sizes in the simulated experiments.
Author(s)
Barbara Kitchenham and Lech Madeyski
Examples
as.data.frame(
calculateNullESAccuracy(
mean=0,sd=1,N=10,reps=30,type='n',seed=123,StdAdj = 0,Blockmean = 0.5))
# Design Obs CliffdAbsError PHatAbsError StdESdAbsError varCliffd varPHat
# 1 2G_n 20 0.20 0.10 0.2624447 0.05530851 0.01382713
# 2 4G_n 20 0.16 0.08 0.1848894 0.05447540 0.01361885
# varStdES ObsCliffd ObsPHat ObsStdES CliffdType1ER PHatType1ER
# 1 0.1425374 0.021333333 0.5106667 0.0001190251 0 0
# 2 0.1484728 -0.009333333 0.4953333 0.0295002335 0 0
# StdESType1ER
# 1 0.03333333
# 2 0.03333333
#as.data.frame(
# calculateNullESAccuracy(
# mean=0,sd=1,N=10,reps=100,type='n',seed=123,StdAdj = 0,Blockmean = 0.5))
# Design Obs CliffdAbsError PHatAbsError StdESdAbsError varCliffd varPHat varStdES ObsCliffd
#1 2G_n 20 0.21 0.105 0.3303331 0.08064949 0.02016237 0.2488365 -0.0010
#2 4G_n 20 0.16 0.080 0.2565372 0.05933430 0.01483358 0.1769521 0.0052
# ObsPHat ObsStdES CliffdType1ER PHatType1ER StdESType1ER
#1 0.4995 -0.02395895 0.07 0.08 0.08
#2 0.5026 0.03769940 0.01 0.01 0.02