Countering the Curse of Dimensionality: Exploring Data-generating Mechanisms Through Participant Observation and Mechanistic Modeling.
Countering the Curse of Dimensionality: Exploring Data-generating Mechanisms Through Participant Observation and Mechanistic Modeling.
复制标题
对抗维度的诅咒:通过参与者观察和机制建模探索数据生成机制。
DOI:
10.1097/ede.0000000000001025
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发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Eisenberg,JosephNS
中科院分区:
文献类型:
--
作者:
Hubbard,Alan;Trostle,James;Cangemi,Ivan;Eisenberg,JosephNS
FIGURE. Facilitating causal inference through systematic mechanistic exploration. A, Outcomes of interest to public health are shaped by complex networks of mechanisms. For example, population circulation can affect and be driven by pathogen transmission, and pathogen transmission can alter the structure and dynamics of social networks, which in turn can influence the capacity of communities to adopt health-enhancing behavioral norms. 44 B, Disentangling these mechanisms to ascertain causes presents serious analytical challenges. Faced with the curse of dimensionality, for instance, researchers must rely on assumptions from the outside concerning data-generating mechanisms to select key variables and thereby reduce the dimension of the problem. C, By placing researchers inside system dynamics, participant observation promotes a process of continuous, responsive counterfactual reasoning, without predetermined variables and rigid study designs. Instead, researchers accumulate perceptions and experiences of potentially relevant mechanisms from diverse perspectives. D, Combined with mechanistic modeling, participant observation can facilitate causal inference by guiding the exploration of candidate data-generating mechanisms across different contexts of observation (“transportability”). 45