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UID:20250626T145538EDT-2743o5mo3J@132.216.98.100
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DESCRIPTION:Overview:\n\nThe goal of this workshop is to serve as an introd
 uction to Bayesian models and tools for analyzing missing or partially obs
 erved data. Specifically\, we will cover the different types of missing da
 ta that one can encounter when working on real problems and various approa
 ches for analyzing the incomplete data under different assumptions.  We wi
 ll begin by considering problems where observations for some characteristi
 cs are completely missing in the original dataset. Then we will address Ba
 yesian models for partially observed values\, e.g. for censored or measure
 ment-error contaminated values.\n\nParticipants will get access to several
  worked examples written in STAN\, NIMBLE\, and other R packages (e.g. mit
 ools) that are often used in the analysis of data with missing values. \n
 \nAt the end of this workshop\, you will be able to:\n	   - Understand the 
 different kinds of assumptions one can choose from for missing data models
  with completely missing observations\;\n	   - Understand the importance of
  incorporating appropriate uncertainty in any analysis where there are mis
 sing values\;\n	   - Identify different patterns of missing values for mult
 ivariate datasets and how they affect analyses\;\n	   - Identify different 
 ways that data can be partially observed and the choices of assumptions fo
 r how that occurs\;\n	   - Fit Bayesian models in STAN and NIMBLE to data w
 ith missing values or Bayesian inference in commonly used models.\n\nPre-r
 equisites:\n	   - An undergraduate/graduate introduction to probability\;\n
 	   - Knowledge of R\;\n	   - An introduction to Bayesian statistics and met
 hods.\n\n\nDate: Friday\, 5 May 2023.\n	Time: 10 a.m. to 12 p.m.\n	Location:
  hybrid (in-person at Burnside Hall 1104\, and online via Zoom).\n	Instruct
 or: Prof. Russell Steele\, Dept. of Mathematics and Statistics\, McGill.\n
 \n\n \n\nRegister\n
DTSTART:20230505T140000Z
DTEND:20230505T160000Z
SUMMARY:Bayesian models & missing data
URL:/cdsi/channels/event/bayesian-models-missing-data-
 346488
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