Literaturnachweis - Detailanzeige
| Autor/inn/en | Zhuang, Jie; Chen, Peijie; Wang, Chao; Huang, Liang; Zhu, Zheng; Zhang, Wenjie; Fan, Xiang |
|---|---|
| Titel | Characteristics of Missing Physical Activity Data in Children and Youth |
| Quelle | In: Research Quarterly for Exercise and Sport, 84 (2013), (7 Seiten)
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0270-1367 |
| DOI | 10.1080/02701367.2013.851059 |
| Schlagwörter | Physical Activities; Error of Measurement; Statistical Data; Gender Differences; Age Differences; Body Weight; Children; Youth; Data Analysis; Data Processing; Measurement Equipment; Classification; Statistical Studies; Research Problems; Foreign Countries; India |
| Abstract | Purpose: The purpose of this study was to investigate the characteristics of missing physical activity (PA) data of children and youth. Method: PA data from the Chinese City Children and Youth Physical Activity Study ("N" = 2,758; 1,438 boys and 1,320 girls; aged 9-17 years old) were used for the study. After the data were sorted by the weekday (WD) and recording day (RD), the missing ratio (MR) was calculated by gender, age, and body mass index (BMI). Chi-square tests were used to determine the effect of WD and RD on missing data. The joint impact (WD × RD) on the MR, as well as their interactions with age, gender, and BMI, were also analyzed. Results: Out of a total of 19,306 records, 5,400 (28.0%) were missing. The total MR significantly differed by WD and RD. There were more missing data during weekend days than during WDs, with the highest being on Sunday (36.2%). Older youth (aged 15-17 years old) had more missing data than did the 9- to 11-year-old group and 12- to 14-year-old group. In terms of RD, the 7th day had the most total missing data (36.0%), and again, older youth (15-17 years old) had more missing data than did the other 2 age groups. Gender and BMI had no impact on missing data by WD or RD. When the joint effect of WD and RD was examined, it was found that providing the measurement devices on Thursday and collecting data from Friday onward resulted in the lowest amount of missing data (18.5%). Conclusion: This study examined missing data characteristics with different sorting orders, which may help design more effective measures to prevent missing data in future PA measurement using accelerometers. (As Provided). |
| Anmerkungen | Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2017/4/10 |
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