summaryCGM.fn {CGManalyzer}

Function to calculate the summary statistics for each subject or sensor: number of subjects or sensors, minimum, 1st quartile, median, mean, 2nd quartile, maximum, standard deviation, MAD

Description

Function to calculate the summary statistics for each subject or sensor: number of subjects or sensors, minimum, 1st quartile, median, mean, 2nd quartile, maximum, standard deviation, MAD

Usage

summaryCGM.fn(dataFolder, dataFiles, responseNames, sensorIDs, columnNames = NULL,
skip = 0, header = TRUE, comment.char = "", sep = ",")

Arguments

dataFolder

folder directory for holding raw CGM data

dataFiles

file names for holding raw CGM data, usually one file for one sensor

responseNames

name for the response

sensorIDs

ID's for sensors

columnNames

column names for the raw data

skip

number of lines to be skip in data file when using read.table

header

the same as in read.table()

comment.char

the same as in read.table()

sep

the same as in read.table()

Details

Function to calculate the summary statistics for each subject or sensor: number of subjects or sensors, minimum, 1st quartile, median, mean, 2nd quartile, maximum, standard deviation, MAD

Author(s)

Xiaohua Douglas Zhang

References

Zhang XD, Zhang Z, Wang D. 2018. CGManalyzer: an R package for analyzing continuous glucose monitoring studies. Bioinformatics 34(9): 1609-1611 (DOI: 10.1093/bioinformatics/btx826).

Examples

library(CGManalyzer)
package.name <- "CGManalyzer"
source( system.file("SPEC", "SPECexample.R", package = package.name) )
summary.arr <- summaryCGM.fn(dataFolder, dataFiles, responseName, sensorIDs, columnNames,
              skip=Skip, header=Header, comment.char=Comment.char, sep=Sep)
summary.arr[1:6, ,1]