infinite-dataset-hub/LongitudinalCaring

‘LongitudinalCaring’数据集旨在探究随着时间的推移善良行为与公共卫生结果之间的关系。该数据集记录了个体在不同时间点接触与善良相关的行为和活动的程度，以及这些活动如何与各种健康指标相关联。数据集的纵向特性允许分析随时间变化的混杂效应，即过去对善良行为的暴露可能影响正在研究中的暴露和健康结果。数据集包括各种潜在的混杂变量，如社会经济地位、年龄、性别和先前健康状况，以便在分析中控制它们的影响。

The LongitudinalCaring dataset is designed to explore the relationship between kindness and public health outcomes over time. It tracks individuals exposure to kindness-related behaviors and activities across different time periods and how these correlate with various health metrics. The longitudinal nature of the dataset allows for the analysis of time-varying confounding effects, where past exposure to kindness could influence both the exposure and health outcomes under study. The dataset includes various potential confounding variables such as socioeconomic status, age, gender, and prior health conditions to control for their effects in the analysis.