每日时间路径：一种对时间日记数据的潜在类别分析方法。
Daily Temporal Pathways: A Latent Class Approach to Time Diary Data.
作者信息
Flood Sarah M, Hill Rachelle, Genadek Katie R
机构信息
Minnesota Population Center, University of Minnesota, Twin Cities, 50 Willey Hall, 225 19th Avenue South, Minneapolis, MN 55455, USA.
Minnesota Federal Statistical Research Data Center, U.S. Census Bureau, 50 Willey Hall, 225 19th Avenue South, Minneapolis, MN 55455, USA.
出版信息
Soc Indic Res. 2018 Jan;135(1):117-142. doi: 10.1007/s11205-016-1469-0. Epub 2016 Oct 15.
Research on daily time and how it is allocated has generally considered the time spent in specific activities. However, social theory suggests that time use is socially patterned whether by social organization, heterogeneity, and/or stratification. Drawing on four broad types of time (contracted, committed, necessary, and free), we use Multinomial Logit Latent Class Analysis to discuss eight daily temporal pathways and associations with individual characteristics. Our analysis highlights the variations and similarities across pathways, the impact of paid work in structuring daily life, the social patterning of sleep and leisure, and socio-demographic profiles of the pathways of working-age Americans.
关于日常时间及其分配方式的研究通常关注特定活动所花费的时间。然而，社会理论表明，无论时间使用是由社会组织、异质性和/或分层所塑造，它都具有社会模式。基于四种广泛类型的时间（约定时间、承诺时间、必要时间和自由时间），我们运用多项逻辑潜在类别分析来探讨八种日常时间路径以及它们与个体特征的关联。我们的分析突出了各路径之间的差异和相似之处、有偿工作对构建日常生活的影响、睡眠和休闲的社会模式，以及美国工作年龄人群时间路径的社会人口统计学特征。
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