Kang Minsoo, Rowe David A, Barreira Tiago V, Robinson Terrance S, Mahar Matthew T
Department of Health and Human Performance, Middle Tennessee State University, Murfreesboro, TN 37132, USA.
Res Q Exerc Sport. 2009 Jun;80(2):131-7. doi: 10.1080/02701367.2009.10599546.
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.
本研究的目的是使用118个数据样本验证以个体信息（II）为中心的缺失数据处理方法。我们采用半模拟方法创建了六个数据集：两组（即中年成年人和老年人）的三种身体活动结果测量指标（即步数、活动计数以及中度至剧烈身体活动的分钟数）。在分别分析每个数据集后，我们用两种以II为中心和两种以组信息（GI）为中心的方法替换缺失值。使用均方根差（RMSD）、平均符号差、配对t检验和Pearson相关性来确定各种恢复方法的有效性。总体而言，在两组的每个数据集中，以II为中心的方法显示出比以GI为中心的方法更小的RMSD。我们发现在所有条件下已知值和替换值之间没有显著的平均差异。以II为中心的方法比以GI为中心的方法产生了更好的结果。我们确定，对于中年成年人和老年人的计步器及加速度计数据，使用剩余天数的平均值来替代缺失数据点是一种准确的缺失数据恢复方法。
