2023 Fall Meetings

Fall Semester, 2023

September 12 (11:30 am, University Office Plaza, Room 2-240)

Division Working Group Introductions The Division of Biostatistics hosts several working groups which focus on different topics of interest for our faculty and students. This seminar will offer brief presentations from faculty/student leads of each working group summarizing the topic they cover and their group’s structure. Attendees will learn about the division’s research focuses and how to join each working group. 

September 29 (10:00 am, University Office Plaza, UOP Statdale Conference Room and Zoom)

Topic: A crush course on survival analysis by Ryan Shanley

Reference: Emily C. Zabor, Survival Analysis in R, URL: https://www.emilyzabor.com/tutorials/survival_analysis_in_r_tutorial.html

October 13 (10:00 am, University Office Plaza, Skylab in Room 351 and Zoom)

Topic: Discuss Dr. Taylor's talk on Tuesday, "Using Joint Models for Longitudinal and Time-to-Event Data to Investigate the Causal Effect of Salvage Therapy after Prostatectomy."

Reference: Rizopoulos D, Taylor J, Morgan TM, Using Joint Models for Longitudinal and Time-to-Event Data to Investigate the Causal Effect of Salvage Therapy after Prostatectomy.

November 3 (10:00 am, University Office Plaza, Skylab in Room 351 and Zoom)

Topic: Justin Clark willl present on "Simulating survival data with simIDM." Slides.

Reference: Erdmann A, Beyersmann J, Rufibach K. Oncology clinical trial design planning based on a multistate model that jointly models progression-free and overall survival endpoints. 2023, arXiv:2301.10059v1.

November 17 (10:00 am, University Office Plaza, Skylab in Room 351 and Zoom)

Michelle Sonnenberger (and Dr. Tom Murray) will be talking about discrete time survival modeling, specifically using a person-period dataset, and go over examples of Bayesian discrete time survival models along with applications to her current research.

References: 

• Suresh K, Severn C, Ghosh D. (2022). Survival prediction models: an introduction to discrete-time modeling. BMC Medical Research Methodology, 22:207.

• Singer JD, Willett JB. (1993). It's about time: using discrete-time survival analysis to study duration and the timing of events. Journal of Educational Statistics, 18(2):155-195.

December 1 (10:00 am, University Office Plaza, Skylab in Room 351 and Zoom)

Han Lu will talk about her current research on left-truncated, right-censoring data. (Contact Han for slides.)

References: 

• Eaton A, Sun Y, Neaton J, Luo X. (2022). Nonparametric estimation in an illness-death model with component-wise censoring. Biometrics, 2022 Sep; 78(3):1168-1180.

• Wolfson DB, Best AF, Addona V, Wolfson J, Gadalla SM. (2019). Benefits of combining prevalent and incident cohorts: An application to myotonic dystrophy. SMMR, 28(10-11):3333-3345.

December 15 (10:00 am, University Office Plaza, Skylab in Room 351 and Zoom)

Dr. Anne Eaton will lead a hack-a-thon about inverse probability of censoring weighting to account for dependent censoring.

References: Willems S, Schat A, van Noorden MS, Fiocco M. Correcting for dependent censoring in routine outcome monitoring data by applying the inverse probability censoring weighted estimator. Stat Methods Med Res. 2018 Feb;27(2):323-335.