The seminars are open to PhD students and post doc researchers working in the field of medical epidemiology at Uppsala University. In a friendly atmosphere we discuss around different methodological topics. More senior researchers are of course welcome to participate in the seminars but are kindly asked to keep mostly in the background to allow space for a discussion at the level of the PhD students.
Preparation for the seminar is encouraged by reading the suggested literature. The seminars are during the current circumstances held online via Zoom only. Since the seminars are based on your active participation in the discussion around the topic, we encourage that you have a working webcam and headset.
Information on the seminars will be posted on this website and via a mailing list. To subscribe to the mailing list, go to https://lists.uu.se/sympa/subscribe/surgsci-episeminars. Feel free to recommend the list and the website to others you think might be interested in participating. You can manage your lists and unsubscribe at lists.uu.se. A Zoom link for each seminar will be distributed via the email list.
This year, the epidemiology seminars can be taken as a PhD student course (info here). Attendance to 10 seminars will merit 1 hp. An attendance list will be circulated at each seminar.
Contact Liisa Byberg if you have suggestions for topics to discuss during the seminars or if you have further questions: firstname.lastname@example.org.
Seminars Autumn 2022
1-2 pm, on Zoom
Wednesday 7 September: Adjustment for multiple comparisons
During this seminar we will discuss item number 5 on Rothman’s list of persistent research misconceptions, “One should always report P values or confidence intervals that have been adjusted for multiple comparisons”. Prepare for the seminar by reading item number 5 in Rothman, J Gen Intern Med 2014 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4061362/) and for a more in depth discussion, also see Rothman, Epidemiology 1990 (https://www.jstor.org/stable/20065622).
Wednesday 21 September: Misclassification bias
Misclassification is a common issue in epidemiology. We will base our discussions on a paper by JJ Yland et al: Misconceptions About the Direction of Bias From Nondifferential Misclassification. American Journal of Epidemiology, Volume 191, Issue 8, August 2022, Pages 1485–1495, https://doi.org/10.1093/aje/kwac035. If you do not have the time to read the full paper, read the introduction and then focus on one of the exceptions to the commonly stated “nondifferential misclassification biases estimates towards the null” that you have encountered (or expect to encounter) in your research.
Wednesday 28 September: Non-differential misclassification of confounders
Misclassification is a common issue in epidemiology. What happens if there is misclassification in a confounder? There is a vast and rather complex literature on the topic. We will have a discussion at a basic level regarding this issue. Prepare for the seminar by reading the introduction in this otherwise non-basic paper on the topic by Ogburn & VanderWeele, Epidemiology 2012 (http://dx.doi.org/10.1097/EDE.0b013e31824d1f63)
Wednesday 12 October: Introduction to understanding the notation used in causal inference papers
Much of the methodological development in epidemiology occurs within the field of causal inference. We have in previous seminars encountered such and with some guidance to deciphering the notation and formulas, we can better understand such papers without going into the mathematical theory. As a preparation for this seminar, I suggest you read Chapter 1 (sections 1.1-1.3) of Miguel Hernáns book Causal Inference: What If, available for free download from his website: https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ This gives a background to the topic and we will have a closer look at the measures of causal effect and exemplify using the notation in previous seminar’s paper by Ogburn & VanderWeele, Epidemiology 2012 (http://dx.doi.org/10.1097/EDE.0b013e31824d1f63).
Wednesday 2 November
Group-based trajectory modelling is becoming an attractive statistical method in studies with longitudinal data. In the next seminar Emerald Heiland (Dept of Surgical Sciences) will introduce this approach and give an example from her own research. You can read this non-technical article “Group-based trajectory modeling in clinical research” (Nagin & Odgers 2010 Annu Rev Clin Psychol) https://doi.org/10.1146/annurev.clinpsy.121208.131413 in preparation for the seminar, which is also a good starting point if you are interested in this method.
Wednesday 23 November: Cohort study participation, nonresponse, and attrition
At this seminar Emerald Heiland (Dept of Surgical Sciences) will lead us in a discussion about cohort study participation, nonresponse, and attrition based off of the study by Taanila et al. https://jech.bmj.com/content/76/12/1019 and the commentary by Bu https://jech.bmj.com/content/76/12/971. Come ready to share your experiences and thoughts!
Wednesday 7 December
Previous seminars (SPRING 2022)
1-2 pm, on Zoom (until further notice).
Wednesday 16 February 2022
This seminar will focus on selection bias in cohort studies. Specifically, we will discuss what selection bias from loss to follow-up is, why it is a threat to cohort studies, and some approaches we can take to assess and minimize it. We will address some of these issues by discussing the article by Howe LD et al. Epidemiology 2013 ”Loss to follow-up in cohort studies: Bias in estimates of socioeconomic inequalities” (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5102324/). The seminar will be hosted by Emerald Heiland, Dept of Surgical Sciences.
Tuesday 1 March 2022
The topic of this seminar is study designs and will focus on the different types of study designs and explore them in terms of their application and feasibility and challenges. It also aims to reflect and discuss the study designs we are currently employing in our research. The article “Observational studies: a review of study designs, challenges and strategies to reduce confounding” by Lu CY published in the Int J of Clinical Practice in 2009 will form the basis for our discussion. https://doi.org/10.1111/j.1742-1241.2009.02056.x. The seminar will be hosted by Stanley Teleka, Dept of Surgical Sciences.
Wednesday 16 March 2022
During this seminar we will discuss interaction and effect modification. Prepare for the seminar by reading this paper by Alhbom & Alfredsson: https://link.springer.com/article/10.1007/s10654-005-4410-4. Think about examples from your own research and reflect on the purposes for investigating effect modification and interaction in studies. The seminar will be hosted by Stanley Teleka, Dept of Surgical Sciencces.
Wednesday 30 March 2022
Imputation of missing data. To impute or not to impute? At the next seminar we will discuss common multiple imputation misconceptions. Choose 1 or 2 of the 6 misconceptions mentioned in the attached paper, and come ready to discuss your thoughts and share your experiences https://www.tandfonline.com/doi/full/10.1080/00223891.2018.1530680. The seminar will be hosted by Emerald Heiland, Dept of Surgical Sciences.
Thursday 28 April 2022
At this seminar we will discuss compositional data. Michael Fridén, Dept of Public Health and Caring Sciences, will give an introduction and we suggest that you prepare for the seminar by reading this paper by Arnold et al https://pubmed.ncbi.nlm.nih.gov/32154892/ and by thinking about whether you are using any compositional data in your own research.
Wednesday 11 May 2022
Proteomics is a rapidly growing field of research, and proteomics approaches are applied in investigation of disease pathways, identification of novel biomarkers for different health outcomes, detection of drug targets etc. Olga Titova, Department of Surgical Sciences, will give an introduction to proteomics analysis with focus on Olink proteomics. We suggest that you have a look at the mini-review by Rojo et al. https://pubmed.ncbi.nlm.nih.gov/34512391/ and share your experience if you have used omics techniques in your research.
Tuesday 24 May 2022 (new date!)
Composite outcomes. There is a lot of literature on this topic and I picked a short paper: https://www.jclinepi.com/article/S0895-4356(20)30850-7/fulltext Read the paper and think about whether you use composite outcomes in your research or have encountered situations where they have worked well, or didn't work well...