The two intensive two-day doctoral courses are divided in 4 daily sessions of 75 min each, taught by world-class faculty amongst an international crowd of participants. We will also offer two special sessions across the two courses, where transversal topics will be addressed:

day 1: visualization options in QCA: overview and pro's and con's and day 2: formatting of a QCA paper for submission to a journal (tips & good practices).

For the introductory level course: No prior knowledge is required. However, basic knowledge of research design is desirable to follow the course. If in doubt, contact the instructors before participating. For the intermediate level course: some prior knowledge is required; in particular: (1) knowledge of the epistemological foundations of QCA; (2) having followed some introductory-level QCA training, or having acquired equivalent skills through self-learning; 

(3) some hands-on experience in applying QCA, including software use (at least basic protocols). In addition, some knowledge of the basic functions of R and RStudio will be useful to start working with the software from session 1. If in doubt, contact the instructors before registering.

Each doctoral course is worth 3 credits (pass/fail grade). In order to be awarded the credits, registered participants will need to fully attend the course (90% attendance), participate in-class activities, doing necessary reading and/or other work prior to, and after, class. A take-home paper will need to be prepared (2500–4000 words, excluding title page, references and appendices), 

which will consist of a replication of a published QCA study (with TOSMANA software or R environment) or a QCA analysis based on own data. More information about assignments will be provided in class.