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DESCRIPTION:Title: Multi-State Survival Models and Dementia\n\nAbstract: Dr
 . Therneau grew up on a dairy farm in southeast Minnesota. He received his
  PhD from Stanford in 1983\, and has been a member of the Biostatistics di
 vision at Mayo Clinic since 1985. He is coauthor of the book 'Modeling Sur
 vival Data'\, a fellow of the American Statistical Association\, and recip
 ient of the 2020 W.J. Dixon award for excellence in statistical consulting
 . He first started writing S software to support his analyses in 1984\, wh
 ich effort grew into the survival package in R. He also enjoys woodworking
 \, bicycling\, and canoeing in the BWCA. Five grandchildren may be his gre
 atest delight and reward.\n\n\nI am a statistician who works in medical re
 search\, and I am also the author of the R survival package. This talk is 
 a direct result of that three way interaction and also will have three int
 ersecting threads. Medical question and data. What are the patterns of dea
 th and dementia in a general population\, as a function of age and sex\, a
 nd what is the impact of select other factors\, e.g.\, amyloid accumulatio
 n\, on these patterns? How do the factors interact in their effect? Data i
 s from the Mayo Clinic Study of Aging\, an age and sex stratified random s
 ample from Olmsted County\, Minnesota. The results tell a fascinating stor
 y. Statistical models. New problems drive new approaches. This analysis is
  based on multi-state hazard models\, a fairly straightforward extension o
 f the ordinary Cox model. In this analysis there are only 3 states (not de
 mented\, dementia\, death) and three possible transitions between states. 
 Nevertheless\, this simple extension a provides much richer insight into t
 he process. (In the last few years multi-state models have supplanted Cox 
 models as my primary analysis tool.) Software. New methods create new soft
 ware. The survival package is my 'daily driver'\, so any new statistical m
 ethod inevitably leads to an attempt to make the approach easy to use and 
 reliable. In this case the target has been to make multi-state models as s
 imple as coxph\, and multi-state outcomes as easy to display as survfit. S
 oftware will only be touched on in this talk\, however\, with said materia
 l deferred to a later tutorial.\n
DTSTART:20210331T193000Z
DTEND:20210331T203000Z
SUMMARY:Terry M. Therneau\, PhD\, Mayo Clinic
URL:/mathstat/channels/event/terry-m-therneau-phd-mayo
 -clinic-329604
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