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‘nparACT’ package for R: A free software tool for the non-parametric analysis of actigraphy data

Overview of attention for article published in MethodsX, May 2016
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Article details
Title
‘nparACT’ package for R: A free software tool for the non-parametric analysis of actigraphy data
Published in
MethodsX, May 2016
DOI 10.1016/j.mex.2016.05.006
Pubmed ID
Authors
Abstract

For many studies, participants' sleep-wake patterns are monitored and recorded prior to, during and following an experimental or clinical intervention using actigraphy, i.e. the recording of data generated by movements. Often, these data are merely inspected visually without computation of descriptive parameters, in part due to the lack of user-friendly software. To address this deficit, we developed a package for R Core Team [6], that allows computing several non-parametric measures from actigraphy data. Specifically, it computes the interdaily stability (IS), intradaily variability (IV) and relative amplitude (RA) of activity and gives the start times and average activity values of M10 (i.e. the ten hours with maximal activity) and L5 (i.e. the five hours with least activity). Two functions compute these 'classical' parameters and handle either single or multiple files. Two other functions additionally allow computing an L-value (i.e. the least activity value) for a user-defined time span termed 'Lflex' value. A plotting option is included in all functions. The package can be downloaded from the Comprehensive R Archives Network (CRAN). •The package 'nparACT' for R serves the non-parametric analysis of actigraphy data.•Computed parameters include interdaily stability (IS), intradaily variability (IV) and relative amplitude (RA) as well as start times and average activity during the 10 h with maximal and the 5 h with minimal activity (i.e. M10 and L5).

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The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 137 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 21 15%
Student > Ph. D. Student 19 14%
Student > Master 10 7%
Student > Doctoral Student 9 7%
Student > Bachelor 7 5%
Other 22 16%
Unknown 49 36%
Readers by discipline
Readers by discipline Count As %
Psychology 15 11%
Neuroscience 12 9%
Agricultural and Biological Sciences 11 8%
Medicine and Dentistry 11 8%
Computer Science 6 4%
Other 23 17%
Unknown 59 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 June 2016.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from MethodsX
#741
of 898 outputs
Outputs of similar age
#304,644
of 348,784 outputs
Outputs of similar age from MethodsX
#10
of 12 outputs
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