g.report.part4 {GGIR}

Generate report from milestone data produced by g.part4

Description

Creates report from milestone data produced by g.part4. Not intended for direct use by package user

Usage

g.report.part4(datadir = c(), metadatadir = c(), loglocation = c(), f0 = c(),
  f1 = c(), data_cleaning_file = c(),
  sleepwindowType = "SPT", params_output, verbose = TRUE)

Arguments

datadir

Directory where the accelerometer files are stored, e.g. "C:/mydata", or list of accelerometer filenames and directories, e.g. c("C:/mydata/myfile1.bin", "C:/mydata/myfile2.bin").

metadatadir

Directory that holds a folder 'meta' and inside this a folder 'basic' which contains the milestone data produced by g.part1. The folderstructure is normally created by g.part1 and GGIR will recognise what the value of metadatadir is.

loglocation

see g.part4

f0

File index to start with (default = 1). Index refers to the filenames sorted in alphabetical order

f1

File index to finish with (defaults to number of files available, i.e., f1 = 0)

data_cleaning_file

see GGIR

sleepwindowType

see GGIR

params_output

Parameters object, see GGIR

verbose

See details in GGIR.

Value

Function does not produce data, but only writes reports in csv format and a visual report in pdf.

The following files are stored in the root of the results folder: part4_nightsummary_sleep_cleaned.csv part4_summary_sleep_cleaned.csv

The following files are stored in the folder results/QC: part4_nightsummary_sleep_full.csv part4_summary_sleep_full.csv

If a sleeplog is used *_full.csv as stored in the QC folder includes estimates for all nights in the data, and *_cleaned.csv in the results folder includes estimates for all nights in the data excluding the nights that did not had a sleeplog entry or had no valid accelerometer data.

If a sleep log is not used then * _cleaned.csv includes the nights that are in *_full.csv excluding the nights with insufficient data.

If you have a study where the sleeplog was available for a subset of the participants, but you want to include all individuals in your analysis, then use the *_full.csv output and clean the night level data yourself by excluding rows with cleaningcode > 1 which are the cases where no or invalid accelerometer data was present.

The above means that for studies with missing sleeplog entries for some individuals and some nights using the *_full.csv output and excluding rows (nights) with cleaningcode > 1 will lead to the same as * _cleaned.csv plus sleep estimates for the nights with missing sleeplog, providing that there was enough accelerometer data for those nights.

In other words, *_cleaned.csv is perfect if you only want to rely on nights with a sleeplog or if you do not use a sleeplog at all. For all other scenarios We advise using the *_full.csv report and to clean it yourself.

See package vignette sections "Sleep analysis" and "Output part 4" for a more elaborative description of the sleep analysis and reporting.

Author(s)

Vincent T van Hees <[e-mail]>