Do you want to know more about novel methods in epidemiology but don’t have the time read a bunch of papers on the topic? Do you want to keep current on the latest developments but can’t go back to school for another degree? Do you just want the big picture understanding so you can follow along? SERious EPI is a new podcast from the Society for Epidemiologic Research hosted by Hailey Banack and Matt Fox. The podcast will include interviews with leading epidemiology researcher who are experts on cutting edge and novel methods. Interviews will focus on why these methods are so important, what problems they solve, and how they are currently being used. The podcast is targeted towards current students as well as practicing epidemiologists who want to learn more from experts in the field.
S2E15: As random as it gets
In this episode of Season 2 of SERious Epidemiology, Hailey and Matt finally start talking about random error. We explore the deep philosophical (as deep as we are capable of) meaning behind randomness and whether the universe is a random (and hey, while we are at it, is there even free will) and how we think about random error. We talk about p-hacking and p-curves and anything p really. And we talk about precision and accuracy in epidemiologic research. And Hailey aces Matt’s quiz.
S2E14: Confounding will never go away – with Maya Mathur
In this episode of Season 2 of SERious Epidemiology, Hailey and Matt connect with Dr. Maya Mathur for a discussion on confounding. We talk about different ways of thinking about confounding and we discuss how different sources of bias can come together. We talk about overadjustment bias, a topic we all feel needs more attention. We discuss e-values, and have Dr. Mathur explain their practical utility and also how complicated they are to interpret. And we discuss bias analysis for meta-analyses.
Article mentioned in this episode:
Schisterman EF, Cole SR, Platt RW. Overadjustment bias and unnecessary adjustment in epidemiologic studies. Epidemiology. 2009 Jul;20(4):488-95. doi: 10.1097/EDE.0b013e3181a819a1. PMID: 19525685; PMCID: PMC2744485.
S2E13: Confounding: Ten thousand arrows going into a bunch of squiggly things
In this episode of Season 2 of SERious Epidemiology, Hailey and Matt discuss confounding and whether confounding is hogging the spotlight in epi methods and epi teaching. We debate the value of all the different terms for confounding in the world of epi and beyond and struggle to define them all. We talk about different definitions for confounding and we differentiate between confounders and confounding. We talk about the 10% change in estimate of effect approach and its limitations and we talk about different strategies for confounder control. And Hailey coins the term “DAGmatist”.
We reference the paper below:
VanderWeele, T.J. and Shpitser, I. (2011). A new criterion for confounder selection. Biometrics, 67:1406-1413.
S2E12: How great are case-control studies with Ellie Matthay
In this episode of Season 2 of SERious Epidemiology, (recorded back when we were getting COVID booster shots) Hailey and Matt connect with Dr. Ellie Matthay for a discussion on Chapter 8 on case-control studies. We finally answer whether it is spelled with a – or not (and Hailey and Ellie disagree with Matt about semicolons). We discuss how cohort studies and case control studies differ and overlap. We talk about whether case control studies are more biased than cohort studies. And Hailey reveals her dreams for releasing Modern Epidemiology: the Audiobook (with possible singing).
S2E11: Case Control Studies
In this episode of Season 2 of SERious Epidemiology, Hailey and Matt get into the humble case control study. We discuss the ins and outs of this much maligned study design that has so flummoxed so many in epidemiology. We ask the hard questions about the best way sample in a case control study, whether we spend too much or not enough time on it in our teaching, whether a case control study always has to be nested within some hypothetical cohort, whether the design is inherently more biased than cohort studies (spoiler: no, but…), why some people refer to cases and controls when they are not referring to a case control study, and, if it were on a famous TV show, which character the case control study would be (and more importantly, why Hailey has never seen said TV show).
Papers referenced in this episode:
Selection of Controls in Case-Control Studies: I. Principles
Sholom Wacholder, Joseph K. McLaughlin, Debra T. Silverman, Jack S. Mandel
American Journal of Epidemiology, Volume 135, Issue 9, 1 May 1992, Pages 1019–1028, https://doi.org/10.1093/oxfordjournals.aje.a116396
Selection of Controls in Case-Control Studies: II. Types of Controls
Sholom Wacholder, Debra T. Silverman, Joseph K. McLaughlin, Jack S. Mandel
American Journal of Epidemiology, Volume 135, Issue 9, 1 May 1992, Pages 1029–1041, https://doi.org/10.1093/oxfordjournals.aje.a116397
Selection of controls in case-control studies. III. Design options
S Wacholder 1, D T Silverman, J K McLaughlin, J S Mandel
Wacholder S, Silverman DT, McLaughlin JK, Mandel JS. Selection of controls in case-control studies. III. Design options. Am J Epidemiol. 1992 May 1;135(9):1042-50.
S2E10: The Return of the Cohort Studies
In this episode of Season 2 of SERious Epidemiology, Hailey and Matt get some real world experience with cohort studies in a conversation with Dr. Vasan Ramachandran, PI of the Framingham Heart Study (FHS). FHS is a very well-known cohort study and the model that many of us have in mind when we think of cohort studies. We get a bit of history on FHS and Hailey and I have a chance to ask the questions we have struggled with around cohort studies including the role of representativeness. And, spoiler alert, we learn that FHS did not invent the term “risk factor” as Matt has been telling his students for years.
Great methods resource for students!
I’m a PhD in Biological Anthropology and MPH in Epidemiology student. Because epi is not my primary field of study and my training is more applied and MPH-level (rather than more research intensive as would be the case in PhD epi courses), this podcast has been a great supplement for digging deeper into epi research methods and causal inference!