ExtractGroupSizeData {reproducer} | R Documentation |
ExtractGroupSizeData
Description
This function constructs a table identifying the number of participants in each sequence group for a set of experiments each of which used a crossover design.
Usage
ExtractGroupSizeData(
ExpDataWide,
StudyID,
ShortExperimentNames,
Type,
Groups = c("A", "B", "C", "D")
)
Arguments
ExpDataWide |
this is a list of tibbles each comprising data from one experiment in its wide format |
StudyID |
an identifier for the group of related experiments (i.e., a family). |
ShortExperimentNames |
a list of character strings identifying each experiment. |
Type |
A list identifying the type of crossover '2G' or '4G' for each experiment in the family |
Groups |
a list of the terms used to specify sequence groups in the experiments. |
Value
A tibble containing the number of participants in each sequence group in each experiment.
Author(s)
Barbara Kitchenham and Lech Madeyski
Examples
ExperimentNames <- c("EUBAS", "R1UCLM", "R2UCLM", "R3UCLM")
ShortExperimentNames <- c("E1", "E2", "E3", "E4")
Metrics <- c("Comprehension", "Modification")
Type <- c("4G", "4G", "4G", "4G")
Groups <- c("A", "B", "C", "D")
StudyID <- "S2"
Control <- "SC"
# Obtain experimental data from a file and put in wide format
dataset2 <- KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14TOSEM
ReshapedData <- ExtractExperimentData(dataset2,
ExperimentNames = ExperimentNames,
idvar = "ParticipantID", timevar = "Period", ConvertToWide = TRUE
)
ExtractGroupSizeData(ReshapedData, StudyID, ShortExperimentNames, Type, Groups = Groups)
# A tibble: 16 x 4
# Study Exp Group n
# <chr> <chr> <chr> <int>
# 1 S2 Exp1 A 6
# 2 S2 Exp1 B 6
# 3 S2 Exp1 C 6
# 4 S2 Exp1 D 6
# 5 S2 Exp2 A 6
# 6 S2 Exp2 B 6
# 7 S2 Exp2 C 5
# 8 S2 Exp2 D 5
# 9 S2 Exp3 A 5
# 10 S2 Exp3 B 5
# 11 S2 Exp3 C 6
# 12 S2 Exp3 D 6
# 13 S2 Exp4 A 5
# 14 S2 Exp4 B 5
# 15 S2 Exp4 C 4
# 16 S2 Exp4 D 4
[Package reproducer version 0.5.3 Index]