Understanding variability in time spent in selected locations for 7-12-year old children.
Understanding variability in time spent in selected locations for 7-12-year old children.
复制标题
了解 7-12 岁儿童在选定地点花费的时间的变化。
DOI：
10.1038/sj.jea.7500319
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
Ozkaynak,Haluk
中科院分区：
文献类型：
--
作者：
Xue,Jianping;McCurdy,Thomas;Spengler,John;Ozkaynak,Haluk
本文总结了哈佛大学对南加州 160 名 7-12 岁儿童收集的聚类、连续活动/位置数据的一系列分析（Geyh 等，2000）。本文的主要目的是了解样本在室外位置所花费的时间的内部和相互之间的变异性，该位置在评估的位置中表现出最大的变异性。使用无分布假设检验（分布的 K-S 检验）、广义线性建模技术和随机抽样方案来分析数据，随机抽样方案产生“队列”，其描述性统计特征根据原始数据集进行评估。最重要的是，我们的分析表明，将人群细分为适当的群组可以更好地复制原始数据的参数，包括类间相关系数（ICC），它是原始数据固有的个体内和个体内变异性的相对度量。虽然我们的分析结果与之前对“时间预算”和身体活动数据的评估一致，但它们受到我们可用的相当同质样本的限制。由于普遍缺乏其他年龄/性别群体的纵向人类活动/位置数据，我们无法将我们的发现推广到其他人口亚组。
This paper summarizes a series of analyses of clustered, sequential activity/location data collected by Harvard University for 160 children aged 7–12 years in Southern California (Geyh et al., 2000). The main purpose of the paper is to understand intra-and inter-variability in the time spent by the sample in the outdoor location, the location exhibiting the most variability of the ones evaluated. The data were analyzed using distribution-free hypothesis-testing (K–S tests of the distributions), generalized linear modeling techniques, and random-sampling schemes that produced “cohorts” whose descriptive statistical characteristics were evaluated against the original dataset. Most importantly, our analyses indicate that subdividing the population into appropriate cohorts better replicates parameters of the original data, including the interclass correlation coefficient (ICC), which is a relative measure of the intra-and inter-individual variability inherent in the original data. While the findings of our analyses are consistent with previous assessments of “time budget” and physical activity data, they are constrained by the rather homogeneous sample available to us. Owing to a general lack of longitudinal human activity/location data available for other age/gender cohorts, we are unable to generalize our findings to other population subgroups.