Mixed data analysis: Advanced integration techniques

Anthony J. Onwuegbuzie, John R. Slate, Nancy L. Leech, Kathleen M.T. Collins

Research output: Contribution to journalArticlepeer-review

78 Citations (Scopus)

Abstract

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 publishedstudies 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 coherentlyand make meta-inferences that have interpretive consistency.

Original languageEnglish
Pages (from-to)13-33
Number of pages21
JournalInternational Journal of Multiple Research Approaches
Volume3
Issue number1
DOIs
Publication statusPublished - Apr 2009
Externally publishedYes

Keywords

  • Case-oriented analyses
  • Mixed analysis
  • Mixed data analysis
  • Mixed research
  • Process/experience-oriented analyses
  • Three-dimensional analyses
  • Variable-oriented analyses

ASJC Scopus subject areas

  • Education

Fingerprint

Dive into the research topics of 'Mixed data analysis: Advanced integration techniques'. Together they form a unique fingerprint.

Cite this