Dataset for "Analysing longitudinal wearable physical activity data using Non-stationary Time Series models"

1416 80 18163 4 70633 document 18163 Hourly_SedTime.csv application/csv 04d199780dca8ac54c9ca3dc3ed4de73 MD5 9317694 2024-07-17 15:42:28 https://researchdata.bath.ac.uk/1416/3/Hourly_SedTime.csv 1416 3 3 application/csv other This dataset contains physical activity data used for analysis in “Analysing longitudinal wearable physical activity data using Non-stationary Time Series models”. See Readme file for details. en public cc_by

Hourly_SedTime.csv

data 18164 2 70638 document 18164 Readme.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document bd87e19d897efb31dd4e3c7c265dfc85 MD5 17213 2024-07-17 15:44:02 https://researchdata.bath.ac.uk/1416/4/Readme.docx 1416 4 4 application/vnd.openxmlformats-officedocument.wordprocessingml.document other en public cc_by

Readme.docx

documentation 18165 1 70640 document 18165 indexcodes.txt text/plain c92b4121a00408084cb53e9dc2be42de MD5 903 2024-07-17 15:51:20 https://researchdata.bath.ac.uk/1416/5/indexcodes.txt 1416 5 5 text/plain other Generate index codes conversion from other to indexcodes en public

indexcodes.txt

http://eprints.org/relation/isVersionOf https://researchdata.bath.ac.uk/id/document/18164 http://eprints.org/relation/isVolatileVersionOf https://researchdata.bath.ac.uk/id/document/18164 http://eprints.org/relation/isIndexCodesVersionOf https://researchdata.bath.ac.uk/id/document/18164 archive 13255 disk0/00/00/14/16 2025-06-09 14:44:50 2025-07-04 06:38:56 2025-06-09 14:44:50 data_collection show Del Angel Martinez Melina Nohemi mndam20@bath.ac.uk 0000-0002-3958-5769 University of Bath TRUE Thompson Dylan spsdt@bath.ac.uk 0000-0002-6312-1518 University of Bath FALSE Nunes Matthew man54@bath.ac.uk 0000-0002-4719-2690 University of Bath FALSE Dataset for "Analysing longitudinal wearable physical activity data using Non-stationary Time Series models" GJ0090 dept_health Physical Activity, Wearable data analysis, Wearable devices, Trend estimation, Longitudinal Study, Longitudinal data analysis, Non-stationary time series, TLSW, High resolution data, Sedentary time This dataset contains secondary data from the Multidimensional Individualised Physical Activity (MIPACT) randomized controlled trial used for analysis in “Analysing longitudinal wearable physical activity data using Non-stationary Time Series models”. Physical activity data over the 12-week intervention for 80 participants (28 women) aged between 43 and 70 years old is presented in this dataset at hourly resolution. 2025-06-09 University of Bath public RightsHolder University of Bath University of Bath https://doi.org/10.13039/501100000835 Doctoral Studentship cent_cnem Full details of the methodology for collecting the minute resolution data are provided in the published study protocol. The raw data was aggregated to obtain the number of minutes spent in sedentary time per hour ("Sedentary"). This aggregated data is presented in the current dataset. The raw data was processed using the statistical software R (version 4.3.0). The resulting dataset is saved in CSV format and can be opened with any software that supports CSV files, including Microsoft Excel. https://doi.org/10.1186%2Fs13063-015-0892-x en 1 10.15125/BATH-01416 https://doi.org/10.15125/BATH-00713 data https://doi.org/10.1186/s12966-025-01779-8 pub open