calculateGroupSummaryStatistics: calculateGroupSummaryStatistics

In reproducer: Reproduce Statistical Analyses and Meta-Analyses

calculateGroupSummaryStatistics

Description

This function calculates the following statistics data within groups: length, mean, median, variance, standard error of the mean, and confidence interval bounds.

Usage

calculateGroupSummaryStatistics(x, Group)

Arguments

x	The data to be summarized. This must be a vector of 2 or more numerical values
Group	The categorical data data defining the groups. This must vector of the same length as x containing factors specifying the data groups

Value

A dataframe comprising the number, mean, variance, standard error and confidence limit bounds of the data in each category

Author(s)

Barbara Kitchenham and Lech Madeyski

Examples

ShortExperimentNames <- c("E1", "E2", "E3", "E4")
FullExperimentNames <- c("EUBAS", "R1UCLM", "R2UCLM", "R3UCLM")
Metrics <- c("Comprehension", "Modification")
Groups <- c("A", "B", "C", "D")
Type <- c(rep("4G", 4))
StudyID <- "S2"
Control <- "SC"
ReshapedData <- ExtractExperimentData(
  KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14TOSEM,
  ExperimentNames = FullExperimentNames, idvar = "ParticipantID", timevar = "Period",
  ConvertToWide = TRUE
)
NewTable <- ConstructLevel1ExperimentRData(
  ReshapedData, StudyID,
  ShortExperimentNames, Groups, Metrics, Type, Control
)
SeqGroupLev <- NULL
N.NT <- length(NewTable$r)
for (i in 1:N.NT) {
  if (NewTable$n[i] <= 8) SeqGroupLev[i] <- as.character(NewTable$n[i])
  if (NewTable$n[i] > 8) SeqGroupLev[i] <- as.character(9)
}
calculateGroupSummaryStatistics(NewTable$r, Group = SeqGroupLev)
#     N    Mean  Median Variance  StDev     SE
#  1  4 -0.0833 -0.1699   0.2314 0.4810 0.2405
#  2 12  0.3658  0.4477   0.2109 0.4592 0.1326
#  3 16 -0.1300 -0.2214   0.1933 0.4397 0.1099

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