定量分析(化学)
多元方法论
认知重构
一致性(知识库)
计算机科学
代表(政治)
定性分析
变量(数学)
定性性质
维数(图论)
数据科学
定性研究
数据分析
过程(计算)
数据挖掘
心理学
数学
社会学
人工智能
机器学习
社会心理学
社会科学
数学教育
法学
政治学
数学分析
化学
操作系统
色谱法
政治
纯数学
作者
Anthony J. Onwuegbuzie,John R. Slate,Nancy L. Leech,Kathleen M. T. Collins
出处
期刊:International Journal of Multiple Research Approaches
[Dialectical Publishing]
日期:2009-04-01
卷期号:3 (1): 13-33
被引量:121
标识
DOI:10.5172/mra.455.3.1.13
摘要
The purpose of this paper is to provide a coherent and inclusive framework for conducting mixed analyses. First, we present a two-dimensional representation for classifying and organizing both qualitative and quantitative analyses. This representation involves reframing qualitative and quantitative analyses as either variable-oriented or case-oriented analyses, yielding a 2 (qualitative analysis phase vs. quantitative analysis phase) × 2 (variable-oriented analysis vs. case-oriented analysis) mixed analysis grid. We present a comprehensive list of specific qualitative (e.g. method of constant comparison) and quantitative (e.g. multiple regression) analyses that fit under each of the four cells. Next, we provide an even more comprehensive framework that incorporates a time dimension (i.e. process/experience-oriented analyses), yielding a 2 (qualitative analysis phase vs. quantitative analysis phase) × 2 (particularistic vs. universalistic; variable-oriented analysis) × 2 (intrinsic case vs. instrumental case; case-oriented analysis) × 2 (cross-sectional vs. longitudinal; process/experience-oriented analysis) model. Examples from published studies are presented for each of these two representations. We contend that these two representations can help mixed researchers – both novice and experienced researchers alike – not only classify qualitative, quantitative and mixed research, but, more importantly, can help them both design their mixed analyses, as well as analyze their data coherently and make meta-inferences that have interpretive consistency.
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