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Statistical analysis of life history calendar data

机译:生活历日历数据的统计分析

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摘要

The life history calendar is a data-collection tool for obtaining reliable retrospective data about life events. To illustrate the analysis of such data, we compare the model-based probabilistic event history analysis and the model-free data mining method, sequence analysis. In event history analysis, we estimate instead of transition hazards the cumulative prediction probabilities of life events in the entire trajectory. In sequence analysis, we compare several dissimilarity metrics and contrast data-driven and user-defined substitution costs. As an example, we study young adults' transition to adulthood as a sequence of events in three life domains. The events define the multistate event history model and the parallel life domains in multidimensional sequence analysis. The relationship between life trajectories and excess depressive symptoms in middle age is further studied by their joint prediction in the multistate model and by regressing the symptom scores on individual-specific cluster indices. The two approaches complement each other in life course analysis; sequence analysis can effectively find typical and atypical life patterns while event history analysis is needed for causal inquiries.
机译:生命历史日历是一种数据收集工具,用于获取有关生命事件的可靠追溯数据。为了说明对此类数据的分析,我们比较了基于模型的概率事件历史分析和无模型数据挖掘方法,序列分析。在事件历史分析中,我们估计而不是过渡危害是整个轨迹中生活事件的累积预测概率。在序列分析中,我们比较了几种差异指标,并对比了数据驱动和用户定义的替代成本。例如,我们以三个生活领域中的一系列事件来研究年轻人向成年的过渡。这些事件定义了多维状态分析中的多状态事件历史模型和并行生命域。通过在多状态模型中的联合预测以及通过对个体特定聚类指数的症状评分进行回归,可以进一步研究中年生活轨迹与过度抑郁症状之间的关系。两种方法在生命历程分析中是相辅相成的。序列分析可以有效地找到典型的和非典型的生活模式,而因果关系查询则需要事件历史分析。

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