Working with Longitudinal Qualitative Data: Using NVivo as an Analytic Tool

1. Working with Longitudinal Qualitative Data: Using NVivo as an Analytic Tool Roger J. VallanceThe University of Notre Dame Australia Paper presented at the 6th International conference of Qualitative Research Conference, 21-23 Sept 2005 Durham.

2. Longitudinal Qualitative research • Research question • Longitudinal qualitative research occurs when a research question investigating a development over time or causal perspective is conducted in a qualitative methodology • Research sample • Research methodology

3. Sampling • Repeated cross-sectional samples • Same questions asked of different samples over time. • Panel study (different styles of panels explored below) • Same individuals are interviewed repeatedly over time. • Indefinite life panel without replacement • Once a group of participants are enlisted, the group participants are re-contacted for each iteration of the research. • Indefinite life panel with replacement • As above • Rotating panel • Sample strategies calls for the research to last longer than average participation. Participants might be included for 3 or 4 iterations and then replaced according to the same sample choices as original sample selection. • Overlapping panel • Use of several rotating panel structures so that groups are out of phase in their replacement cycles.

4. LQR methodologies • Not restricted to specific methodologies • That said, LQR does not happen by accident • Distinction between longitudinal and meta-analysis • Research question • Sample • maybe not approach to analysis and synthesis

5. Organising the Data • Attributes • Information that is relatively unchanging, • That might form a table of values organised in columns for each participant (row) • Sets • Used for more ad hoc or volatile information • Overlapping data sets • Cases • Cases nodes for testing emergent ideas

6. Attributes in longitudinal analysis

7. Sets in longitudinal analysis

8. Cases in longitudinal analysis

9. Three useful distinctions • Theme • Manifest statements of individual participants • Participant perspective • Pattern • Findings of the research, possibly pro term • Researcher perspective • Topic • Summary of contributions and discussions with participants. • cf Luborsky 1994 The Identification and Analysis of Themese and Patterns, in J.F. Gubrium & A. Sankar Qualitative Methods in Aging Research. Sage.

10. Longitudinal Analysis • Ideally, unit of analysis is the individual • Analysing each wave • At this point in time What is the qual analysis ? • Connecting between the waves • What has changed and how have these changes occurred • Retrospection • How did we come to this? • Participant validation • At end of research, chance to validate their stories

11. Sets scope searches

12. Connecting between the waves

13. Bringing it together • Retrospection • Looking back over one’s shoulder • Epiphanies • Turning points • Dead ends and discontinuities • Participant validation • Not always possible • And what does one validate? • Individual analysis • More global views

14. One view of Longitudinal Qualitative Analysis • What has changed? • How has it changed? • For whom has it changed? • Why has it changed? • How have they changed? • Where /who are they now?

15. A second view of Longitudinal Qualitative Analysis • What has changed for these participants? [subQ – for this person] • Analyse topics and individual accounts • What has caused these observed changes? • Analyse themes with field notes • To what extent are these changes global? • Analyse patterns with field notes and memos

16. New horizons • Qualitative data is growing in volume, richness, number, extent to which we can cope with large data collections • Historical inspections of similar projects possible • Warehousing of data may yield resource of great value • Might interoperation of CAQDAS be another step?