Causal cycles, causal intervals, and measurement in over-time studies
指出纵向研究中测量间隔应与因果间隔匹配，通过飓风、工作变动和技术采用三个例子说明，并为匹配测量与因果间隔提供建议。
If over-time data are used to model XàY causal relationships, the measurement (or “recording”) interval should match (or at least approximate) the actual causal (or “existence”) interval for X’s effect on Y. I discuss this issue in the context of causal cycles of events and give three examples involving hurricanes, job change and adoption and implementation of new technology. I conclude with some considerations and recommendations for matching measurement to causal intervals in over-time research.