TY - JOUR
T1 - Integrating mixed methods data analysis using NVivo : an example examining attrition and persistence of nursing students
AU - Andrew, Sharon
AU - Salamonson, Yenna
AU - Halcomb, Elizabeth J.
PY - 2008
Y1 - 2008
N2 - 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 (SPSSâ„¢) Version 13.0 and the qualitative data was imported into NVivo. In the next stage attribute data for each participant was imported from SPSSâ„¢ 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.
AB - 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 (SPSSâ„¢) Version 13.0 and the qualitative data was imported into NVivo. In the next stage attribute data for each participant was imported from SPSSâ„¢ 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.
UR - http://handle.uws.edu.au:8081/1959.7/555967
UR - http://search.informit.com.au/documentSummary;res=IELHSS;dn=133133561253859
M3 - Article
SN - 1834-0806
VL - 2
SP - 36
EP - 43
JO - International Journal of Multiple Research Approaches
JF - International Journal of Multiple Research Approaches
IS - 1
ER -