Integrating Mixed Methods Data Analysis Using NVivo: An example examining attrition and persistence of nursing students
Sharon Andrew
School of Nursing and Midwifery, University of Western Sydney, Campbelltown Campus, Sydney NSW
Yenna Salamonson
School of Nursing and Midwifery, University of Western Sydney, Campbelltown Campus, Sydney NSW
Elizabeth J Halcomb
School of Nursing and Midwifery, University of Western Sydney, Sydney NSW
PP: 36 - 43
Abstract
The use of mixed methods research is growing in popularity in a range of disciplines, although the literature provides few descriptions of the practical aspects of mixing qualitative and quantitative data in the one study. Perhaps the greatest complexity in mixed method research is achieving integration of qualitative and quantitative data.
This paper explores how NVivo Version 2.0 was used to facilitate data analysis in a mixed methods study of student attrition and retention in a Bachelor of Nursing program. Quantitative data was initially entered into Statistical Package for the Social Sciences (SPSSTM) Version 13.0 and the qualitative data was imported into NVivo. In the next stage attribute data for each participant was imported from SPSSTM into NVivo. The coded qualitative data were then explored for relationships with participants' attribute profile (marital status, Family Support).
The use of NVivo software proved to be beneficial in facilitating the synthesis of the mixed methods data and enriched the findings of the study by adding another dimension to the data. The lessons learnt from this experience will assist other researchers in investigating alternative tools for integrating mixed methods data.
Keywords
mixed methods, data analysis, methodology, computer aided data analysis, NVivo
Article Text
The value of collecting qualitative and quantitative data in the form of mixed methods research is being increasingly recognised (Andrew & Halcomb 2006). To date, mixed methods research designs have predominately been comparative, convergent or sequential in nature, with priority given to one type of data (Creswell & Plano Clark 2007; Teddlie & Tashakkori 2003). While established methods and computer programs to assist with the analysis of qualitative and quantitative data separately have been long established, there have not been clear methods available for the integration of data from mixed methods research. Rather, this has relied on the creativity of the researcher in developing new or adapting existing approaches to mixed data.
Developments in computer technology have now facilitated the fusion of qualitative and quantitative data into a single data set (Bazeley 1999; Bazeley 2002). This has enabled the researcher to undertake truly integrated data analysis, thus achieving a degree of richness of data that was previously not available. The use of computers in the collection, management and analysis of qualitative (Fielding & Lee 1998; Gibbs 2002; Hutchinson 2005; Roberts & Woods 2000) and quantitative (Coakes 2006; Manning 2006) data has been explored in the literature. However, while the computer technology that facilitates mixed methods data analysis is becoming increasingly available, the literature provides limited practical guidance on how such integration can be practically achieved (Prein & Kuckartz 1995).
This paper will explore how NVivo was used as a tool for facilitating data analysis in a mixed methods study of student attrition and retention amongst third year students enrolled in a Bachelor of Nursing (BN) program in a regional Australian university.
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