reproducer (version 0.5.2)

simulate2GExperimentData: simulate2GExperimentData

Description

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

Usage

simulate2GExperimentData(
  mean,
  sd,
  diff,
  GroupSize,
  type = "n",
  ExpAdj = 0,
  StdAdj = 0,
  BlockEffect = 0,
  BlockStdAdj = 0
)

Value

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

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 dentifying the distribution used to simulate the data: 'n' for normal, 'ln' for log-normal, 'g' for gamma, 'lap' for Laplace.

ExpAdj

An additional adjustment factor that is added to both the mean value. Defaults to zero.

StdAdj

An additional adjustment factor that is added to both group variance (or rate for gamma data). Defaults to zero.

BlockEffect

An additional factor that is added to the mean of the both groups (shape for the gamma distribution). Defaults to zero.

BlockStdAdj

An additional factor that is added to the variance of both groups (shape for the gamma distribution). Defaults to zero.

Author

Barbara Kitchenham and Lech Madeyski

Examples

set.seed(236)
simulate2GExperimentData(mean = 0, sd = 1, diff = 0.5, GroupSize = 10,
  type = "n", ExpAdj = 0, StdAdj = 0, BlockEffect = 0, BlockStdAdj = 0)
# A tibble: 10 x 2
#    BaselineData AlternativeData
#                      
#                     
# 1      -0.285           -0.255
# 2      -0.972            0.112
# 3      -0.549            1.36
# 4       1.05             1.47
# 5      -0.267            0.107
# 6      -0.137            0.395
# 7       1.30             1.27
# 8      -0.722            1.70
# 9      -0.525            0.264
# 10      -0.0222           0.787
set.seed(345)
simulate2GExperimentData(mean = 0, sd = 1, diff = 0.5, GroupSize = 10,
  type = "l", ExpAdj = 0, StdAdj = 0, BlockEffect = 0, BlockStdAdj = 0)
# A tibble: 10 x 4
#    BaselineData AlternativeData transBaselineData transAlternativeData
#                                                  
# 1        0.456          10.7             -0.785                 2.37
# 2        0.756           0.407           -0.280                -0.900
# 3        0.851           0.705           -0.161                -0.350
# 4        0.748           2.27            -0.291                 0.818
# 5        0.935           4.07            -0.0675                1.40
# 6        0.531           0.405           -0.634                -0.903
# 7        0.395           2.91            -0.928                 1.07
# 8        5.53            4.69             1.71                  1.55
# 9        5.23            0.602            1.65                 -0.508
# 10        6.11            2.23             1.81                  0.802