Systematic Sampling, Temporal Aggregation, and the Study of Political Relationships
Systematic Sampling, Temporal Aggregation, and the Study of Political Relationships
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系统抽样、时间聚合和政治关系研究
DOI：
10.1093/pan/1.1.61
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发表时间：
1989
影响因子：
5.4
通讯作者：
John R. Freeman
中科院分区：
文献类型：
--
作者：
John R. Freeman
系统抽样和时间汇总分别是定期对时间序列进行抽样和对一段时间内的时间序列观测值进行求和或平均的做法。这两种做法都是统计错误和错误推断的来源。讨论了系统采样和时间聚集对强指定模型和弱指定模型的构造所产生的问题。这些问题的严重性可以从关于超级大国竞争的辩论中得到说明。这场争论的部分原因是，一些研究人员采用了高度时间聚合的美国和苏联外交政策行为的措施。更大的方法学教训是，我们需要投入更多的时间来确定我们的理论的自然时间单位，并进行跨时间聚合水平的鲁棒性检查。
Systematic sampling and temporal aggregation are the practices of sampling a time series at regular intervals and of summing or averaging time series observations over a time interval, respectively. Both practices are a source of statistical error and faulty inference. The problems that systematic sampling and temporal aggregation create for the construction of strongly specified and weakly specified models are discussed. The seriousness of these problems then is illustrated with respect to the debate about superpower rivalry. The debate is shown to derive, in part, from the fact that some researchers employ highly temporally aggregated measures of U.S. and Soviet foreign policy behavior. The larger methodological lessons are that we need to devote more time to determining the natural time unit of our theories and to conducting robustness checks across levels of temporal aggregation.