simulate4GExperimentData: simulate4GExperimentData

In reproducer: Reproduce Statistical Analyses and Meta-Analyses

simulate4GExperimentData

Description

The function returns a four group data set based on one of four different distributions.

Usage

simulate4GExperimentData(
  mean,
  sd,
  diff,
  GroupSize,
  type = "n",
  ExpAdj = 0,
  StdAdj = 0,
  BlockEffect = 0,
  BlockStdAdj = 0
)

Arguments

mean	The mean (or rate for gamma data) of the baseline distribution
sd	The standard deviation (or shape for gamma data) of the baseline distribution
diff	The adjustment to the baseline mean for the alternative distribution.
GroupSize	An integer defining the number of data items in each group.
type	A string identifying the distrubtion used to simulate the data: 'n' for normal, 'l' for log-normal, 'g' for gamma, 'lap' for Laplace.
ExpAdj	An additional adjument factor that is added to both the mean values. Defaults to zero.
StdAdj	An aditional adjustment factor that is added to the second group variance (or rate for gamma data). Defaults to zero.
BlockEffect	An additional factor that is added to the mean of the second group groups (shape for the gamma distribution). Defaults to zero.
BlockStdAdj	An additional factor that is added to the variance of the second group (shape for the gamma distribution). Defaults to zero.

Value

A table with four columns (BaselineData.B1, AlternativeData.B1,BaselineData.B2, AlternativeData.B2,) holding the data for each group and block. For lognormal data an additional four columns are added which return the log transformed data for each group.

Author(s)

Barbara Kitchenham and Lech Madeyski

Examples

set.seed(246)
simulate4GExperimentData(mean = 0, sd = 1, diff = 0.5, GroupSize = 5,
  type = "n", ExpAdj = 0, StdAdj = 0, BlockEffect = 0.5, BlockStdAdj = 0)
# A tibble: 5 x 4
#  BaselineData.B1 AlternativeData.B1 BaselineData.B2 AlternativeData.B2
#            <dbl>              <dbl>           <dbl>              <dbl>
# 1          0.533               1.84            0.749              3.98
# 2          0.251               2.03            1.56               1.09
# 3         -0.290               0.929           0.213              3.94
# 4         -1.48                1.17            1.13               0.106
# 5          0.0340              0.895           0.399              0.879
as.data.frame(
  simulate4GExperimentData(
    mean=0, sd=1, diff=0.5, GroupSize=5, type='l', ExpAdj=0, StdAdj=0,
    BlockEffect = 0.5, BlockStdAdj = 0))
#  BaselineData.B1 AlternativeData.B1 transBaselineData.B1 transAlternativeData.B1
#1       1.4019869           1.049158            0.3378905               0.0479875
#2       3.8514120           0.769227            1.3484398              -0.2623692
#3       6.5162726           1.574126            1.8743025               0.4537002
#4       1.3309218           1.082774            0.2858718               0.0795259
#5       0.2772234           1.630194           -1.2829316               0.4886992
#  BaselineData.B2 AlternativeData.B2 transBaselineData.B2 transAlternativeData.B2
#1       5.4656049          4.6095688            1.6984748               1.5281343
#2       1.6149559          2.0244244            0.4793077               0.7052854
#3       1.7718620          0.5504016            0.5720310              -0.5971070
#4       0.6774067          1.5434812           -0.3894834               0.4340404
#5       0.4507284          5.4987830           -0.7968903               1.7045268

reproducer documentation built on Oct. 18, 2023, 5:10 p.m.