Collaboration in grounded theory analysis: Reflections and practical suggestions

Abstract

Analytic triangulation is a well known strategy to enhance rigor in qualitative research, but little is known about the process to develop and maintain an intellectually vital analytic dyad. As two recent doctoral graduates, we reflect back on our mutually beneficial, interdisciplinary collaboration. We describe pragmatic guidelines to select an effective analytic partner, to structure work sessions, and to respond to the challenges of shifting needs over time. Utilizing specific examples, we address the intellectual, interpretive, and personal benefits of our analytic partnership. Our reflections may be useful for scholars using grounded theory such as doctoral students, early career researchers, as well as faculty who are mentoring doctoral students doing qualitative research.

Keywords

Analysis collaboration dissertation doctoral student grounded theory interdisciplinary qualitative research rigor triangulation

Doctoral research is independent, but it should occur within a mentored relationship with the doctoral committee and dissertation chair (Roldan and Shelby, 2004). In addition to faculty members, peers are useful resources to promote the student’s progress while doing a qualitative dissertation (Bloomberg and Volpe, 2008; Padgett, Mathew and Conte, 2004). This is our account of creating an in-depth analysis partnership to help us move through the academic alphabet from ABD (‘all but dissertation’) to PhD. In this chronicle, we reflect on the dyadic analysis process that we co-created through nine months of data collection, analysis, and writing. We discuss how we picked a partner, how we structured work sessions, how we evolved with challenges, and how this interpersonal process enhanced our individual interpretive and theory building abilities. We hope that sharing our reflections may be useful to other doctoral students, early career scholars, and faculty who are guiding students through the dissertation process.

When we formed our association, we had learned about peer debriefing and support groups (Lincoln and Guba, 1985; Padgett, 1998; Padgett et al., 2004) to protect against bias and support rigor in qualitative research. We had also experienced dissertation support groups and saw that they served a range of intellectual and emotional benefits (Biklen and Casella, 2007; Cone and Artinian, 2009). Additionally, we valued that the structure of these peer facilitated groups created freedom from power differentials inherent in faculty-student interactions (Padgett et al., 2004). However, we had not read or learned about a committed analysis partnership such as ours throughout the many classes, seminars, and workshops on qualitative research that we attended during our doctoral education. Our ongoing analytic dyad was so helpful that we were surprised that we could not find a similar paper in the literature and that this dyadic process is not commonly recommended to doctoral students. Although collaboration and peer support is recommended for doctoral students doing qualitative dissertations (Biklen and Casella, 2007; Bloomberg and Volpe, 2008; Gioia, 2004), we found no published reflections on the collaborative process, nor did we find a practical roadmap to create an analytic partnership.

Charmaz (2006) suggests that writing a manuscript is a social process. Over the months of collaborating, our experience showed us that data analysis was also best served when viewed as a social process, and a close-knit, dyadic one at that. Our analysis partnership was a time-intensive, interactive process of debate, questioning codes and ideas, reflection, returning to the data, and ultimately respecting the analytic interpretation of the principal investigator (PI). Our experience taught us that our unique analytic dyad challenged, clarified, and supported the critical thinking of the PI. However, when all was said and done, the PI was the only one who was truly immersed inside the data and made the final analytic decisions. The partner played the role of sounding board and colleague. By reflecting on our process in practical terms, we hope other doctoral students might benefit professionally and personally, and decrease some of the lonely journey that comes with the pursuit of a doctorate (Bloomberg and Volpe, 2008; Gioia, 2004).

Connecting: Checking out and sizing up

We first met when we were doctoral students at a large, urban research university. The relationship that has since developed was not initially a ‘natural’ or ‘obvious’ match. We were enrolled in different departments which had different levels of institutional support for qualitative research. (Huibrie Pieters (HP) from nursing and Katrina Dornig (KD) from social welfare.) We come from different generations, countries of origin, and we have different first languages. We were studying different topics and our participants came from different populations. But we also shared similarities: both of us are Caucasian, middle class, heterosexual, and married. A particularly valued similarity was that we were both committed to the applied, practice world. We both held Master’s degrees in clinical psychology and we both taught graduate students. We were both situated at the crossroads of social privilege (in terms of culture, class, geography, and generation) that gives us the power to design our lives with time and space to think and write. Upon reflection, we now know that we both also held a particular commitment to study the health of disenfranchised women with constructivist grounded theory. We both valued the view that in the interpretive tradition, researchers need to challenge invisible standpoints to decrease the likelihood that hidden preconceptions, ‘shadows of capitalism, competition, and individualism’ (Charmaz, 2006: 67) enter the analysis.

Although we did not realize it at the time, our initial, informal meetings were perfect opportunities to size each other up. In the busy reality of doing doctoral coursework, it is understandable for doctoral students to bypass opportunities to network with other similarly minded students. However, given the time necessary to assess and select a good partner, it paid off for us to participate in informal qualitative opportunities (monthly qualitative interest groups) and additional qualitative coursework (advanced qualitative research methodology courses) early in the doctoral process.

We both participated in larger qualitative research support groups on an ongoing basis. These groups generally met once per month, were facilitated on a volunteer basis by generous faculty, and responded flexibly to the needs of the student participants. The groups engaged in a range of scholarly, practical, and supportive activities – from reading qualitative articles and texts, to discussing different research methodologies, to coding short segments of interview transcripts, to sharing practical information about qualitative software and technology. While particularly useful early in our qualitative education, the groups did not allow for in-depth, consistent attention to one person’s dataset.

Then, during two quarters of 2008 we had the privilege to work with a professor as part of a three-person research team analyzing existing qualitative data. The PI structured our meetings so that we approached the data from the clearly articulated philosophical perspective of pragmatism and the methodological perspective of constructivist GT (Charmaz, 2006). As part of this analytic triad, we coded, diagrammed, clustered, wrote memos, and simultaneously engaged in ‘theoretical playfulness’ (Charmaz, 2006: 71) to try new ways of viewing the data. In addition to these methodological and practical strategies, the PI exemplified the importance of open debate, questioning our codes, returning to the data, and ultimately respecting the PI’s analytic interpretation. Although we did not realize it at the time, this team analysis, an engaging, spirited, and often heated scholarly process, was highly beneficial for shaping and establishing our future dyadic partnership. It was toward the end of the team coding that KD began to think about inviting HP to be her analytic partner for dissertation data.

Our team research experience working as an analytic triad crystallized the value of clear, congruent methodological practices and an in-depth, time intensive commitment to analysis. As a result, KD invited HP to co-create a dissertation analytic partnership with the following email:

10/13/10 Huibrie,

I’ve been thinking and wanted to float an idea by you about our dissertations. One thing I’ve been meaning to do, and not had time/motivation to do until now, is try to set up a somewhat regular meeting with a dissertation ‘buddy’ where we can review each other’s coding and/or interviews, writing, etc. to help build our rigor and analytic thinking.

I’ve used larger groups at times, but sometimes large groups can be too much input and I end up feeling more flooded and confused – too many well intentioned and smart minds paired with my own always interested in exploring other ideas – not always productive! I’ve so enjoyed working with you, I was wondering if you’d be open to exploring if something like this could be mutually beneficial for us?

Especially since I’m doing a mental health dissertation, and am interested in resilience, I just thought you had a lot of expertise that could help me push my analytic thinking forward. I think you have a particular skill at ‘higher level’, ‘bigger concept’ thinking – which I am trying to build my skills in. …

HP responded as follows:

10/14/08 Dear Katrina,

Wow, your letter was such a great surprise when it arrived last night, but as I try to refrain from impulsive decisions, I slept on the matter. So (note time of this letter) I woke up with a ‘YES’, same as when I read it.

I like, like, like the idea of a ‘group’ of two.

Also, your timeline sounds workable as I cannot take on anything till the end of the year, but am available after that. My research is at the phase of desperately-looking-for-participants as I have only interviewed one woman this far. However, I am actively working on accruing and should have 200 (joke) by January.

So, YES … and thanks for asking!

We consider ourselves fortunate to have had the freedom to select each other. It is not possible to overestimate the importance of choosing an analytic partner who is a good fit. But, in our experience, ‘a good fit’ does not mean ‘an exact replica’. In fact, we discovered that our different skills and attributes were often complementary and beneficial to our analysis

What impressed the two of us about the scholarship of the other was initially left unspoken. Upon reflection, HP was aware that she came from a strong quantitative background, and appreciated that KD had attended more classes and workshops in qualitative methodology. KD, a citizen of the United States, had both a natural and educated understanding of social complexities that came up in the data. From her perspective, KD remembers appreciating HP’s high level, abstract thinking skills. She seemed able to view data from a macro, interpretive lens, while remaining ‘true’ to the data itself. We mutually perceived a healthy self-awareness in the other, an openness to challenge taken for granted assumptions, and an ability to think creatively. Equally important, we also saw the other’s tenacity, discipline, and follow-through, so we knew we would not be wasting our precious time with someone who was not focused. What matters for future analytic dyads will differ for each individual, but the key is to approach choosing a partner as an active and selective process that takes time and careful consideration.

Collaborating

Although we agreed to work together in mid-October, we did not actually meet until the following February. This gap was partly associated with the general slowing down over the holiday season. Of greater importance though was that, similar to most doctoral students, we both had very demanding schedules. (During this time we were both collecting data for our dissertations, analyzing, and we were both working on other research and teaching.) It took significant time, patience, and perseverance to construct a collaboration that would fit into our already full lives, and work for both our personal and scholarly needs.

Preparing to meet

Through a series of ensuing emails, we clarified our needs and developed an initial structure for our meetings. We planned to meet every other Saturday for three hours and divide our time equally between our dissertations. We decided to meet at a venue between our homes. (We lived at opposite ends of a large metropolis, so that our commutes and the meetings took a significant portion of the day.) In addition to coding our own transcript, we made a commitment to spend two hours prior to the meeting doing coding of the other’s transcript. We selected to work at a coffee shop as opposed to one of our homes or on campus.

Looking back, it was important and helpful to start our partnership with a clearly articulated frame in place. Paying attention to structure and process from the beginning also set the tone that communicating about evolving needs and expectations was expected and welcome.

Co-creating our meetings: Interacting

All of our meetings were in person. We were punctual; we were prepared; we had an agenda, and we turned our cell phones off. In retrospect, we realize that meeting regularly at a large coffee shop where many other students were studying also helped us establish an uninterrupted, task oriented approach. Despite becoming friends through this process, at the time we did not socialize outside of our meetings. The analysis itself was the driving motivation for our relationship.

Three days in advance of our meeting, we electronically exchanged a transcript to give the other person sufficient time to do the coding. We coded by hand with pen on paper copies. On the transcript itself, we wrote a brief 3–4 line summary of the interview, noted appreciation of especially well-framed interview questions, highlighted potential in vivo codes, and posed thoughtful questions. We also encouraged one another’s creativity and efforts to utilize additional data analysis tools, such as data matrices (Miles and Huberman, 1994), Atlas ti (Knowledge Workbench, 2009), diagramming (Charmaz, 2006), or situational maps (Clarke, 2005).

Our process continued. In between meetings we emailed reflections, musings, and checked in on how the structure was working for each of us:

08/31/09 Dear Katrina,

On the way home from Saturday’s meeting I felt as if we spend more time with my work than with yours. I did not check the clock so it is possible that my perception is more a reflection of value received (relative to ‘given’) than what a clock may tell us.

Then yesterday when I wrote the final paper, well the final before I send it to (chair of HP’s doctoral committee) at 2.00am this morning (!), I read all your written comments and just thought how well prepared you were. For which I thank you.

The reason for this letter is to say that it is important for me that we keep our collaboration in a healthy balance. Please let me know if you want to just focus on your work or suchlike next time …

09/02/09 Hi Huibrie,

In a bit of a rush today … feeling the pressure of getting a ‘dress rehearsal’ draft to my chair in a week. But I wanted to quickly say, I feel our time is balanced and really benefit from our meetings, we spent a lot of time on my discussion section Sat. Thank you for caring to check in about this. I was thinking about your data on the way home and wondering if I was over complicating things from that nice map you had constructed! Hope your meeting with (chair of HP’s doctoral committee) was fruitful. I really like Self as circle. Do you know that American phrase, ‘she’s so square’ – it connotes really traditional, straight arrow, and a bit prissy (i.e. not much fun!). So, I’m quite sure that’s not the self you want to symbolize in your maps. Your women hardly seem to fit that description!

As reflected in the above emails, our committed, task-oriented partnership evolved to also be emotionally supportive.

Building trust and emotional support

We initially approached our work together motivated by external ideas of analytic triangulation, rigor, trustworthiness, and strong individual scholarship. Our collaboration rewarded these intentions since the ultimate benefit of our process was that it added depth and productivity to our own, independent work. Meeting regularly with someone else who was well acquainted with much of our data, helped both of us more clearly articulate our analytic logic, and develop an audit trail (Lincoln and Guba, 1985). It also helped highlight blind spots or biases we brought to the analyses. As our cooperation continued, it also evolved into a more interpersonal, multi-layered process.

In retrospect, a variety of micro-activities between us communicated support. Regular meetings and continuing to articulate our evolving expectations helped to build trust and commitment. Through the process of analysis, we interacted with each other’s data in an open, respectful and engaged way. We approached coding not to establish the ‘right’ code, but rather with the goal of pushing one another’s analytic thinking forward. Coding during our collaboration was empowering for the very reason that we were free to make ‘mistakes’.

Our emerging partnership proved to be a safe place to ask the kind of questions that we thought we could answer while in classes, but these insights somehow became diluted in the loneliness and stress of the PhD journey. For example, when one of us was deeply immersed in her data during the final phases of theory making, she became stuck on remembering the difference between a category and a subcategory. It was as if her personal hard drive had crashed. She wrote a panicked email to her fellow rookie (as this was too embarrassing to ask her chair!) The answer that promptly arrived provided much relief: ‘Who cares? Just keep on moving!’ It was this psychological reboot, not more information, which was most needed at this time. Throughout this process, we experienced how one learns outside of the classroom from a fellow student, with the freedom to admit ignorance, ask naive questions, and laugh together.

We experienced an intellectual creativity from the lack of hierarchy between two peers. We say this as two students who also benefited greatly from generous and expert chairs. However, even the most supportive of mentors, even those who are acutely sensitive to power differentials, are still cast in the role of educator and expert (with all the privileges and responsibilities that context entails). Two students, by virtue of being students, both hold beginner’s mind. We were early explorers, not experts. We did not yet have the intellectual shorthand that experts have earned through years of hard work and which become almost taken for granted ways of being.

This mutual ‘not knowing’ between the two of us allowed more time in the struggle. We had to sit still with our data simply because we did not have another option; we had not yet discovered the path out! We valued being able to acknowledge our powerlessness to someone we trusted and respected, and who was not there as a formal teacher. Paradoxically, this intellectual struggle in the presence of a supportive other allowed space for creative, deep work and increased individual scholarly confidence. This emotional containment helped us take ownership of our own interpretive skills and theory building capabilities.

Our effective partnership also evolved and progressed because we perceived the other person to care about our data within a shared commitment to women’s health research from a feminist perspective. Our level of focus and commitment to the other’s data made it possible to freely critique one another’s work. We challenged one another’s thinking. We asked and received alternative views from the other. We believe this enhanced our study’s dependability and trustworthiness. The ultimate benefit of our collaborative association was that it added depth and breadth to our theories and moved our individual research forward.

Evolving: Focusing on strengths while navigating challenges

Time and the research process itself naturally brought challenges to our partnership. To keep our collaboration useful, we navigated these challenges from a foundation of shared strengths. Structurally, time worked in our favor as our dissertation activities progressed at a similar pace. We started meeting after we were advanced to candidacy, while we were collecting and analyzing data. We had our last meetings nine months later, shortly before our individual final dissertation defense dates – one week apart.

Both of us know that our evolving analytic partnership helped us complete our dissertations sooner than we would have otherwise done working alone mostly because we helped each other stay on schedule. Practically, the structure and pacing of our bi-weekly meetings increased steadily as external demands intensified. Instead of sharing the time between two data sets, we shifted to dedicate the entire meeting to one person’s analyses. We also extended the length of our meetings from three to four hours. As the level of our analyses was raised, we changed from initial and focused coding to discussing analytic maps, memos, and segments of writing. We sensed that our collaboration helped us to simultaneously be open and messy while we were also thinking systematically and condensing the data (Charmaz, 2006; Clarke, 2005).

Our time investment in the analytic dyad particularly paid off during this last part of our time together. We had helpful discussions about determining data saturation, the challenges of implementing theoretical sampling, and theory making. We were acutely aware of the risk of forcing our theoretical biases onto the data and our discussions helped us reduce our self-oriented projections. Nuanced reflections and questions from the other person were highly valued during this phase because they were grounded in a deep knowing of the other’s data over time, while also retaining an outsider perspective. For example, one of us was considering a category in her data named, ‘being an activist’. The other person noted that ‘activism’ sounded like the PI’s voice, and that it was too broad to represent the nuances in the data that the participants described across cases. She asked a series of questions which prompted the PI to recognize that ‘activism’ was a general, taken for granted construct applied from her profession. Through this interaction, the PI realized that ‘helping other women’ was closer to the data itself. This exchange helped the PI to tease out subcategories and develop a fuller perspective of the category. Interactions such as these helped us gain confidence in our own interpretive decision making.

We knew that despite the significant time commitment, our individual research was ultimately benefiting from our interactions. We were aware that other options would not have been as helpful for us at this time (i.e. working alone and relying on the self-interaction of memo writing only, or working in a less consistent, less in-depth way with a large group). A committed dyadic relationship, in addition to our meetings with our professors, particularly worked for our focused, theory-building needs during this phase of the dissertation process.

Challenges

Utilizing shared strengths helped us to evolve and work with the unforeseen challenges that arose. The three biggest challenges we identified are all different dimensions of time and space: physical, intellectual, and emotional. Maintaining our useful collaboration required active, assertive communication, and dynamic change.

The physical dimension of time and space may seem obvious, or unnecessary to state explicitly, but it was the greatest challenge. Preparing for meetings, commuting, and the meeting itself required a considerable time commitment that had to be balanced with the multiple demands of our lives. It took patience and perseverance to find mutually workable meeting times. We changed days and meeting sites many times when the financial and work situations of our lives shifted. Given the geography of our city, as well as the personal geography of our full lives, meeting regularly was no small feat.

In addition to the physical component of time and space, the intellectual dimension of our partnership also presented challenges. Becoming immersed in a second set of data, while writing a dissertation on your own data, required a level of cognitive stimulation that could be overwhelming. In addition to opening yourself to the other’s data, the act of taking in the other’s depth of thinking about your data required a great deal of ‘brain work.’ It required being comfortable with ambiguity to be able to consider another’s viewpoint, while at the same time finding clarity about one’s own scholarly perspective. For example, despite the fact that we had asked each other for feedback on our theoretical maps, it still stung when our work, often the fruit of hours of labor, was returned with notes and suggestions from a fellow student. We expected this intensity from our chairs, and we got it. But somehow we were surprised when we received it from each other.

One way we managed challenges was by sharing the mindset that analytic discussions were not about being right; rather, they were about pushing each other’s thinking forward. We believed our individual work benefited from this self-other interaction. We were both high achieving students who had internalized the academic mindset of right/wrong. But, within the context of respect and trust that we had co-constructed, we were free to experience that analysis is not about the pursuit of perfection or the search for the ‘right code.’ Instead, we learned that analysis is about interacting with the data in multiple, different ways that support deep, interpretive thought. Learning how to contain complexities, ambiguities, and multiple perspectives helped us to integrate the philosophical assumptions of constructivism into our GT scholarship.

The emotional dimension of time and space was also a challenge to be faced. Both of our datasets contained in-depth, long interviews with socially marginalized women facing major physical and/or emotional health challenges. Interview transcripts contained intense stories of participants experiencing and surviving multiple traumatic events. Becoming involved in the reality of the women’s stories involved taking in the emotional aspects of the other’s data, in addition to one’s own data. Although there were times that we sensed ‘researcher saturation’ (Wray, Markovic and Manderson, 2007: 1398), i.e. burnout, our regular meetings contributed to maintaining our vitality and enthusiasm.

Another emotional challenge occurred when we had to make final editing decisions just before the dates of our final dissertation defense. At that time, each of us respectively shared a plan for tightening up our own dissertation document to make it more succinct. We referred to these as ‘amputations’ because they felt like significant losses of our participants’ voices. Even though each of us knew that space restrictions necessitated these ‘amputations’, it was hard to hear when our partner agreed.

In retrospect, we realize that both of us share clinical backgrounds that may have implicitly impacted how we approached differences or challenges within our partnership. As mental health clinicians, we have both participated in supervision groups (as members and supervisors) that normalize flexibility of needs, being comfortable with differences, containing ambiguities, attention to process and content, and evolving problem solving. While these skills are not the sole domain of clinicians, our hope in this article is to be as transparent as possible so that others may consider how the partnership we are describing might be similar or different for them.

Limitations and practical implications

We both used constructivist GT as the methodology for our research. An analytic partnership may look different for those who are using other approaches to qualitative research. Still, the practical tools of setting up and maintaining a useful analytic dyad such as ours may be helpful to students utilizing a range of qualitative methodologies. (See Table 1 for summary.) Our collaboration certainly helped to prevent common traps during qualitative data collection and analysis such as feelings of confusion, inadequacy, isolation (Bloomberg and Volpe, 2008; Gioia, 2004), and the dreaded condition of ‘analytic paralysis’ (Clarke, 2005: 84).

As we wrote this article, we realized our implicit relational and process biases – that our own individual, analytic thinking would be enhanced by engaging in a scholarly process with another who ‘knew’ our data well and who could thus challenge our own thinking. We are assuming that others will similarly benefit from such a process. This bias echoes a key assumption behind symbolic interactionism (the theoretical perspective which informs our methodology, constructivist grounded theory), i.e. that we make meaning and form knowledge through self/other interaction (Blumer, 1969; Charon, 2007). However, we acknowledge that this particular approach may be the most beneficial for doctoral students who are working from a similar theoretical orientation and/or are doing interpretive work.

One GT tool to assist staying vigilant about the usefulness of the partnership could be to write memos about the relationship itself. The pivotal importance of ‘the extremely private process’ (Glaser, 1998: 180) of memo writing to ask questions of the data has been described as invaluable (Charmaz, 2006; Lempert, 2007; Lipson, 1991). During our meetings we discussed our data-related memos and diagrams, and often wrote additional memos after meeting. Albeit most useful, these memos were limited to the content of our data. It did not occur to us to also memo about the process of our dyad. If we were to do it over again, particularly working within constructivist sensibilities, we would also write memos about the dyadic interaction itself. Of course, as a doctoral student, time is always in short supply so it is important to consider your own cost-benefit analysis of such a suggestion. In our experience, expenditures of time related to our interactions were beneficial and ultimately enhanced our productivity.

Last reflections (for now)

Writing this article meant taking time to reflect and honor the richness of our experience during the final year of our doctoral studies. Many were the days that the dissertation felt like a hideous chronic disease that had crept up on us in the middle of the night. At those darkest of hours, our partnership felt like an important communion, a community of two. Through our work together, we learned that even if it feels like the dissertation is never going to end, it actually is a passing condition!

Table 1.

Strategies for building and maintaining an analytic dyad: Practical tools

Phase of partnership	To do	To ask of self
Connecting: checking out and sizing up	Seek and participate in opportunities to network with other qualitative scholars both during and outside of coursework (e.g. interest groups, lectures, and conferences). Assess potential future partners.	What are my unique needs and expectations from a dyadic analytic collaboration? What unique contributions do I bring to an analytic dyad?
	Consider your research methodology, research values and ethics, needs and goals.	What do I value? What values do I expect in an analytic partner?
	Ponder the feasibility of setting up an analytic collaboration. For example, think about your anticipated timeline and traveling to meetings.	What are my expectations regarding the time frame to complete sections of my research?
	Memo your needs before inviting someone. Cluster or memo your needs from a partner (e.g. perseverance, conceptual reflection, patience). Repeat memo writing as your partnering process continues.	Why am I asking this person to be my analytic partner? Is it for personal connection, professional discipline and/or convenience? What similarities and differences between us could be helpful or could be bothersome? Will this person impact my own process in a productive way? Or not?
	Frame your invitation to a potential partner as an opportunity to explore if a partnership could be mutually useful.
	If someone else invites you, take time to consider your answer along the above guidelines before deciding to work together.
Collaborating: Setting up	Clarify structure, location, and content of meetings.	How far am I prepared to travel given the limitations of time and money? What other demands are on my time (work, school, family) and how might this influence how I structure meetings? Do I want to consider personal get-togethers interspersed with phone and electronic meetings? How much time/brain space am I willing to give before/between meetings?
	Know that it may take some time to set up the practicalities and organize lives to be able to start a partnership.
	Rely on patience, perseverance, and creativity to design the partnership structure that can work for you.
	Clarify approach to coding and data analysis in general.	How similar/different are our approaches to analysis?
	Clarify approach to coding and data analysis in general.	Will we be hand-coding transcripts? Will we use an analysis software package? If so, at what stage of analysis will we use software?
Co-creating meetings: Interacting	Meet regularly, have a clear agenda. Turn off cell phones. Arrive on time and be prepared as per your mutual agreement. Take time to check in on one another’s progress and feelings.	How many days in advance of meeting do each of us want to trade transcripts/documents? What is on my agenda for the day and what is my partner expecting from our meeting?
	Code, diagram, memo, and summarize. Consider making brief process comments, noting particularly well-framed interview questions.	How do I want my partner to interact with my data? What kinds of comments, coding, questions, and notes do I want to receive from my partner? Do I want my partner to make handwritten notes on my transcripts?
	Explore additional data analysis tools (e.g. data matrices, analysis software).
	Approach meetings with goal of enhancing creativity and pushing one another’s analytic thinking forward (not with a right/wrong mentality).
Ask naive questions.
Memo on your collaboration.	How is this partnership helping me move forward in a useful and efficient manner?
Email between meetings to check in on the structure and balance of work sessions. Share insights, thoughts, and a sense of humor!	How is the balance of time working?
Evolving	Focus on strengths while navigating challenges.	What is working? What do I appreciate about the other? What have I learned about myself and/or my data through these interactions? What needs to flex? What needs are/are not being met?
	In the context of shared respect and trust, challenge each other’s thinking. Ask and receive alternative views from the other.	What biases might I be bringing to the analysis/theory building? Where might I be overlooking nuance and multiple dimensions of my data?
	Discuss data saturation and your higher level analytic thinking. Explore your theoretical interpretations. Share your conceptual maps, diagrams, and writing.
	Continue to memo on your partnership process. Discuss changes and challenges to the partnership.	Are our interactions enhancing my confidence in my interpretive and theory building skills? How has my life situation changed over time? How might I need to shift to ensure the association stays useful?

Footnotes

Acknowledgments

We would like to acknowledge our mentors, our dissertation committee members and, in particular, our chairs.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

References

Biklen

Casella

(2007) A Practical Guide to the Qualitative Dissertation, New York: Teachers College Press.

Bloomberg

Volpe

(2008) Completing Your Qualitative Dissertation, Thousand Oaks, CA: SAGE.

Blumer

(1969) Symbolic Interactionism: Perspective and Method, Berkeley, CA: University of California Press.

Charmaz

(2006) Constructing Grounded Theory, Thousand Oaks, CA: SAGE.

Charon

(2007) Symbolic Interactionism: An Introduction, an Interpretation, an Integration, 9th edn. Upper Saddle River, NJ: Pearson Prentice Hall.

Clarke

(2005) Situational Analysis: Grounded Theory after the Postmodern Turn, Thousand Oaks, CA: SAGE.

Cone

Artinian

(2009) Learning Glaserian grounded theory through mentoring and scholarly dialogue. In: Artinian

Giske

Cone

(eds) Glaserian Grounded Theory in Nursing Research, New York: Springer, pp. 73–76.

Gioia

(2004) Mixed methods in a dissertation study. In: Padgett

(ed.) The Qualitative Research Experience, Belmont, CA: Wadsworth/Thomson Learning, pp. 122–150.

Glaser

(1998) Doing Grounded Theory, Mill Valley, CA: The Sociology Press.

10.

Knowledge Workbench (2009) Atlas ti, Germany: Berlin.

11.

Lempert

(2007) Asking questions of the data: Memo writing in the grounded theory tradition. In: Bryant

Charmaz

(eds) The Sage Handbook of Grounded Theory, Thousand Oaks, CA: SAGE, pp. 245–264.

12.

Lincoln

Guba

(1985) Naturalistic Inquiry, Beverly Hills, CA: SAGE.

13.

Lipson

(1991) Use of self in ethnographic research. In: Morse

(ed.) Qualitative Nursing Research: A Contemporary Dialogue, 2nd edn. Rockville, MD: Aspen Publications, pp. 61–75.

14.

Miles

Huberman

(1994) Qualitative Data Analysis, 2nd edn. Thousand Oaks, CA: SAGE.

15.

Padgett

(1998) Qualitative Methods in Social Work Research: Challenges and Rewards, Thousand Oaks, CA: SAGE.

16.

Padgett

Mathew

Conte

(2004) Peer debriefing and support groups. In: Padgett

(ed.) The Qualitative Research Experience, Belmont, CA: Wadsworth/Thomson Learning, pp. 229–239.

17.

Roldan

Shelby

(2004) The role of the mentoring relationship in qualitative research. In: Padgett

(ed.) The Qualitative Research Experience, Belmont, CA: Wadsworth/Thomson Learning, pp. 215–228.

18.

Wray

Markovic

Manderson

(2007) ‘Researcher saturation’: The impact of data triangulation and intensive-research practices on the researcher and qualitative research process. Qualitative Health Research, 17(10): 1392–1402.