title: Individual information-centered approach for handling physical activity missing data.
abstract: The purpose of this study was to validate individual information (II)-centered methods for handling missing data, using data samples of 118. We used a semisimulation approach to create six data sets: three physical activity outcome measurements (i.e., step counts, activity counts, and minutes of moderate to vigorous physical activity) for both groups (i:e., middle-aged adults and older adults). After analyzing each data set separately, we replaced missing values with two II-centered and two group information (GI)-centered methods. Root mean square difference (RMSD), mean signed difference, paired t tests, and Pearson correlations were used to determine the effectiveness of the various recovery methods. Overall, the II-centered methods showed smaller RMSDs than the GI-centered methods for each data set in both groups. We found no significant mean differences between the known values and the replacement values in all conditions. The II-centered methods produced better results than GI-centered methods. We determined substituting missing data points using the average of days remaining to be an accurate missing data recovery method for middle-aged adults' and older adults'pedometer and accelerometer data.
authors: Department of Health and Human Performance, Middle Tennessee State University, Murfreesboro, TN 37132, USA. mkang@mtsu.edu
authors: Minsoo
authors: M
authors: Kang
authors: David A
authors: DA
authors: Rowe
authors: Tiago V
authors: TV
authors: Barreira
authors: Terrance S
authors: TS
authors: Robinson
authors: Matthew T
authors: MT
authors: Mahar
mesh_terms: D000465:Algorithms; D015982:Bias; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation; D009043:Motor Activity; D010043:Outcome and Process Assessment, Health Care / Q000592:standards; D014481:United States; D016138:Walking / Q000706:statistics & numerical data