Bayesian analysis has emerged as a rapidly expanding frontier in qualitative methods. Recent work in this journal has voiced various doubts regarding how to implement Bayesian process tracing and the costs versus benefits of this approach. In this response, we articulate a very different understanding of the state of the method and a much more positive view of what Bayesian reasoning can do to strengthen qualitative social science. Drawing on forthcoming research as well as our earlier work, we focus on clarifying issues involving mutual exclusivity of hypotheses, evidentiary import, adjudicating among more than two hypotheses, and the logic of iterative research, with the goal of elucidating how Bayesian analysis operates and pushing the f...
This article explains the foundational concepts of Bayesian data analysis using virtually no mathema...
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowled...
Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges th...
Bayesian probability holds the potential to serve as an important bridge between qualitative and qua...
We advance efforts to explicate and improve inference in qualitative research that iterates between ...
Copestake, Goertz, and Haggard’s (CGH) “Veil of ignorance Process Tracing” (VPT)—which in essence en...
Social scientists have long recognized the study of evidence from within individual cases as a funda...
Judgements in the real-world often inherently involve uncertainty, from the mundane: "do those cloud...
We confess that the first part of our title is somewhat of a misnomer. Bayesian reasoning is a norma...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal me...
Why is there no consensual way of conducting Bayesian analyses? We present a summary of agreements a...
Qualitative knowledge is about types of things, and their excellences. There are many ways we humans...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
This article explains the foundational concepts of Bayesian data analysis using virtually no mathema...
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowled...
Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges th...
Bayesian probability holds the potential to serve as an important bridge between qualitative and qua...
We advance efforts to explicate and improve inference in qualitative research that iterates between ...
Copestake, Goertz, and Haggard’s (CGH) “Veil of ignorance Process Tracing” (VPT)—which in essence en...
Social scientists have long recognized the study of evidence from within individual cases as a funda...
Judgements in the real-world often inherently involve uncertainty, from the mundane: "do those cloud...
We confess that the first part of our title is somewhat of a misnomer. Bayesian reasoning is a norma...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal me...
Why is there no consensual way of conducting Bayesian analyses? We present a summary of agreements a...
Qualitative knowledge is about types of things, and their excellences. There are many ways we humans...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
This article explains the foundational concepts of Bayesian data analysis using virtually no mathema...
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowled...
Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges th...