Combines output from g.part3 and guider information to estimate sleep variables. See vignette paragraph "Sleep and full day time-use analysis in GGIR" for an elaborate descript of the sleep detection.
g.part4(datadir=c(),metadatadir=c(),f0=f0,f1=f1,idloc=1,
loglocation = c(),colid = 1,coln1 = 2,nnights = 7,
sleeplogidnum=FALSE,do.visual=FALSE,outliers.only = FALSE,
excludefirstlast=FALSE,criterror = 1,includenightcrit=16,
relyonguider=FALSE, relyonsleeplog=FALSE, def.noc.sleep=1,
storefolderstructure=FALSE,overwrite=FALSE,
desiredtz="",data_cleaning_file=c(),
excludefirst.part4=FALSE,excludelast.part4=FALSE)Directory where the accelerometer files are stored or list of accelerometer filenames and directories
Directory that holds a folders 'meta' and inside this a folder 'basic' which contains the milestone data produced by g.part1. The folderstructure is normally created by g.part3. When using g.part4 via g.shell.GGIR then g.shell.GGIR will automatically recognise what the value of metadatadir is, so the user does not need to specify this.
File index to start with (default = 1). Index refers to the filenames sorted in increasing order
File index to finish with (defaults to number of files available)
If value = 1 (default) the code assumes that ID number is stored in the obvious header field. If value = 2 the code uses the character string preceding the character '_' in the filename as the ID number
Location of the spreadsheet (csv) with sleep log information. The spreadsheet needs to have the following structure: one column for participant ID, and then followed by alternatingly one column for onset time and one column for waking time. There can be multiple sleeplogs in the same spreadsheet. The first raw of the spreadsheet needs to be filled with column names, it does not matter what these column names are. Timestamps are to be stored without date as in hh:mm:ss. If onset corresponds to lights out or intention to fall asleep, then it is the end-users responsibility to account for this in the interpretation of the results.
Column number in the sleep log spreadsheet in which the participant ID code is stored (default = 1)
Column number in the sleep log spreadsheet where the onset of the first night starts
Number of nights for which sleep log information should be available. It assumes that this is constant within a study. If sleep log information is missing for certain nights then leave these blank
Should the participant identifier as stored in the sleeplog be interpretted as a number (TRUE=default) or a character (FALSE)?
If g.part4 is run with do.visual == TRUE then the function will generate a pdf with a visual representation of the overlap between the sleeplog entries and the accelerometer detections. This can be used to visualy verify that the sleeplog entries do not come with obvious mistakes.
Relevant for do.visual == TRUE. Outliers.only == FALSE will visualise all available nights in the data. Outliers.only == TRUE will visualise only for nights with a difference in onset or waking time larger than the variable of argument criterror.
If TRUE then the first and last night of the measurement are ignored for the sleep assessment.
Relevant for do.visual == TRUE and outliers.only == TRUE. criterror specifies the number of minimum number of hours difference between sleep log and accelerometer estimate for the night to be included in the visualisation
Minimum number of valid hours per night (24 hour window between noon and noon)
If TRUE then sleep onset and waking time are defined based on timestamps derived from the guider. If participants were instructed NOT to wear the accelerometer during waking hours then set to TRUE, in all other scenarios set to FALSE (default).
Now replaced by relyonguider. Values provided to argument relyonsleeplog will be passed on to argument relyonguider to not preserve functionality of old R script.
The time window during which sustained inactivity will be assumed to represent sleep, e.g. def.noc.sleep=c(21,9). This is only used if no sleep log entry is available. If def.noc.sleep is left blank 'def.noc.sleep=c()' then the 12 hour window centred at the least active 5 hours of the 24 hour period will be used instead. Here, L5 is hardcoded and will not change by changing argument winhr in function g.part2. If def.noc.sleep is filled with a single integer, e.g. def.noc.sleep=c(1) then the window will be detected with the method as described in van Hees et al. 2018 Scientific Reports.
Store folder structure of the accelerometer data
Overwrite previously generated milestone data by this function for this particular dataset. If FALSE then it will skip the previously processed files (default = FALSE).
See g.getmeta
Optional path to a csv file you create that holds four columns: ID, day_part5, relyonguider_part4, and night_part4. ID should hold the participant ID. Columns day_part5 and night_part4 allow you to specify which day(s) and night(s) need to be excluded from part 5 and 4, respectively. So, this will be done regardless of whether the rest of GGIR thinks those day(s)/night(s) are valid. Column relyonguider_part4 allows you to specify for which nights part 4 should fully rely on the guider. See also package vignette.
If TRUE then the first night of the measurement are ignored for the sleep assessment.
If TRUE then the last night of the measurement are ignored for the sleep assessment.
The function does not produce values but generates an RData file
in the milestone subfolder ms4.out which incudes a dataframe
named nightsummary. This dataframe is used in g.report.part4 to create
two reports one per night and one per person. See package vignette
paragraph "Output part 4" for description of all the variables.
van Hees VT, Sabia S, et al. (2018) AEstimating sleep parameters using an accelerometer without sleep diary, Scientific Reports.
van Hees VT, Sabia S, et al. (2015) A novel, open access method to assess sleep duration using a wrist-worn accelerometer, PLoS ONE.
# NOT RUN {
metadatadir = "C:/myfolder/meta" # assumes that there is a subfolder in
# metadatadir named 'ms3.out' containing the output from g.part3
g.part4(metadatadir=metadatadir)
# }
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