View source: R/summaryCGM.fn.R
summaryCGM.fn | R Documentation |
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
summaryCGM.fn(dataFolder, dataFiles, responseNames, sensorIDs, columnNames = NULL,
skip = 0, header = TRUE, comment.char = "", sep = ",")
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() |
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
Xiaohua Douglas Zhang
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).
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]
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