reproducer (version 0.5.2)

calculateNullESAccuracy: 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
)

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.

Arguments

mean

The mean of the baseline distribution.

sd

The standard deviation or shape of the baseline distribution

N

The number of obervations 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

Author

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