选择(遗传算法)
案例选择
计算机科学
采样(信号处理)
光学(聚焦)
航程(航空)
非概率抽样
运筹学
数据科学
管理科学
机器学习
数学
社会学
工程类
人口
医学
物理
人口学
外科
滤波器(信号处理)
光学
计算机视觉
航空航天工程
作者
Jason Seawright,John Gerring
标识
DOI:10.1177/1065912907313077
摘要
How can scholars select cases from a large universe for in-depth case study analysis? Random sampling is not typically a viable approach when the total number of cases to be selected is small. Hence attention to purposive modes of sampling is needed. Yet, while the existing qualitative literature on case selection offers a wide range of suggestions for case selection, most techniques discussed require in-depth familiarity of each case. Seven case selection procedures are considered, each of which facilitates a different strategy for within-case analysis. The case selection procedures considered focus on typical, diverse, extreme, deviant, influential, most similar, and most different cases. For each case selection procedure, quantitative approaches are discussed that meet the goals of the approach, while still requiring information that can reasonably be gathered for a large number of cases.
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