reproducer (version 0.4.0)

ExtractGroupSizeData: 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 identifer 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.

Examples

# NOT RUN {
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
# }