This course will take place over three mornings (10/2/23, 10/4/23, and 10/6/23), 2.5 hours per morning, and will be offered via Zoom. Attendance is required as the course will not be recorded.
This course introduces participants to constructivist grounded theory (CGT). Grounded theory (GT) methods consist of flexible guidelines to fit particular research problems, not to apply mechanically. With these guidelines, you expedite and systematize data collection and analysis. GT methods can assist researchers in making their work more analytic, precise, and compelling.
In this course, following an exploration of the history and development of GT, we examine GT basic guidelines and major strategies, including initial line-by-line and focused coding, the use of gerunds, memoing, diagramming, theoretical sampling, and categorising. Throughout the sessions, there is an emphasis on CGT's epistemological foundation and resultant adaptations to the research process, including regarding the literature review, researcher positionality/ies and reflexivity, and participant involvement.
The course will include a number of hands-on exercises to exemplify, and give participants an opportunity to practice, the strategies being discussed. For the coding exercise, you may bring and use some of your own qualitative data, or if you do not have data yet, some will be supplied. Clear guidelines and support are provided to course participants with regard to all aspects of CGT.
The sessions will utilise CGT readings and resources from Kathy Charmaz, Robert Thornberg, Adele Clarke, and the presenter, Elaine Keane, and will draw on the extensive scholarship of Barney Glaser and Anselm Strauss. A pack of materials will be shared with participants in advance of the course. This course will be of interest to those doing full CGT studies but also to those who may be interested in learning about and potentially using some of the powerful GT strategies (such as coding) in studies with a different overall methodological approach.
The NC TraCS Biostatistics Seminar Series helps clinical and translational researchers collaborate more effectively with consulting biostatisticians by building deeper understanding of key statistical concepts and methods. Researchers then are better able to (1) evaluate relevance of the concept or method for research aim(s) definition and choice of study design; and (2) properly interpret the results of data analysis.
How should we evaluate the results from a quantitative study? A common, but unfortunate way is to examine the p-value. If it's not significant, the study wasn't good; if it's significant, then good; and if it's highly significant, then very good. In this seminar, Jeff Laux, PhD, will introduce Robert Abelson's MAGIC criteria for evaluating quantitative results.
Laux is a consulting biostatistician and research associate with the Biostatistics Service at NC TraCS Institute and an adjunct instructor with the Department of Biostatistics in the Gillings School of Global Public Health.
This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:
Speaker: David M. Murray, PhD
NIH Associate Director for Prevention and Director, NIH Office of Disease Prevention
Moderator: Jonathan C. Moyer, PhD
Statistician, NIH Office of Disease Prevention