定性研究
样品(材料)
样本量测定
采样(信号处理)
冗余(工程)
心理学
计算机科学
管理科学
统计
社会学
数学
工程类
社会科学
操作系统
滤波器(信号处理)
化学
色谱法
计算机视觉
标识
DOI:10.1002/nur.4770180211
摘要
A common misconception about sampling in qualitative research is that numbers are unimportant in ensuring the adequacy of a sampling strategy. Yet, simple sizes may be too small to support claims of having achieved either informational redundancy or theoretical saturation, or too large to permit the deep, case-oriented analysis that is the raison-d'être of qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be put, the particular research method and purposeful sampling strategy employed, and the research product intended.
科研通智能强力驱动
Strongly Powered by AbleSci AI