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定性数据分析的案例内和跨案例方法。

Within-case and across-case approaches to qualitative data analysis.

作者信息

Ayres Lioness, Kavanaugh Karen, Knafl Kathleen A

机构信息

School of Nursing, University of Wisconsin-Madison, K6/250 Clinical Science Center, Madison, WI 53792-2455, USA.

出版信息

Qual Health Res. 2003 Jul;13(6):871-83. doi: 10.1177/1049732303013006008.

Abstract

The generalizations developed by qualitative researchers are embedded in the contextual richness of individual experience. Qualitative data management strategies that depend solely on coding and sorting of texts into units of like meaning can strip much of this contextual richness away. To prevent this, some authors have recommended treating individual accounts as whole cases or stories, but whole cases are difficult to compare with one another when the goal of the research is to develop generalizations that represent multiple accounts. In this article, the authors describe the ways in which three different qualitative researchers combined across-case coding and sorting with a variety of within-case data management and analysis techniques to produce contextually grounded, generalizable findings.

摘要

定性研究人员得出的概括性结论蕴含在个体经历丰富的情境之中。单纯依赖将文本编码并分类为意义相似单元的定性数据管理策略,可能会剥夺许多这种情境丰富性。为防止这种情况,一些作者建议将个体叙述视为完整案例或故事,但当研究目标是得出代表多个叙述的概括性结论时,完整案例彼此之间很难进行比较。在本文中,作者描述了三位不同的定性研究人员如何将跨案例编码和分类与各种案例内数据管理及分析技术相结合,以得出基于情境且具有普遍性的研究结果。

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