The Leeds Institute for Data Analytics is pleased to present the next seminar in our series showcasing data analytics.
The seminar will be held in 8.43x, Worsley Building, at 3pm on Thursday 28th February.
Students of epidemiology are well versed in ways to reduce systematic error (bias) in the design of their studies and to describe random error in the analysis of their studies through confidence intervals and p values. However, students are rarely taught methodologies for quantifying systematic error in their studies. Quantitative bias analysis (QBA) provides a methodology for assessing the impact of bias on study results by making assumptions about the bias parameters. QBA allows for assessment of both the direction and magnitude of systematic error and gives an estimate of effect (or a series of estimates of effect) that would have occurred had the bias been absent, assuming the bias parameters are correct. Such analyses allow investigators to go beyond speculation about the bias in discussion section of manuscripts and can be a powerful tool for quantifying the impact of such biases.
This 2 hour seminar will cover simple bias analysis methods that can be used to gain a better understanding of the impact of unmeasured misclassification (measurement error) on study results (with hints on how this can also be used for other sources of bias). These methods can be applied to nearly any dataset, even summary data presented in the literature. Such approaches lay the foundation for more complicated methods, but by themselves, they act as if the bias parameters are known with certainty. If time allows we will end with probabilistic bias analysis, which requires specification of probability distributions about the bias parameters and then uses Monte Carlo simulations methods to create intervals accounting for the uncertainty in the systematic error.
Matthew Fox, DSc, MPH, is a Professor in the Departments of Epidemiology and Global Health at Boston University. Dr. Fox joined Boston University in 2001. His research interests include treatment outcomes in HIV-treatment programs, infectious disease epidemiology (with specific interests in HIV and pneumonia), and epidemiologic methods. Dr. Fox works on ways to improve retention in HIV-care programs in South Africa from the time of testing HIV-positive through long-term treatment. As part of this work, he is involved in analyses to assess the impact of changes in South Africa’s National Treatment Guidelines for HIV. Dr. Fox also does research on quantitative bias analysis and co-authored a book on these methods, Applying Quantitative Bias Analysis to Epidemiologic Data. He is also the host of a public health journal club podcast called Free Associations designed to help people stay current in the public health literature and think critically about the quality of research studies. He currently teaches a third-level epidemiologic methods class, Advanced Epidemiology as well as two other doctoral level epidemiologic methods courses. Dr. Fox is a graduate of the Boston University School of Public Health with a master’s degree in epidemiology and biostatistics and a doctorate in epidemiology.
17.00-18.00 Networking reception with drinks and nibbles hosted in the LIDA staff kitchen
Our seminars are free and open to all but places must be booked in advance.
To book a seat please email Hayley Irving with your name, position and faculty/organisation.