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UID:20250919T091511EDT-16651ncPuV@132.216.98.100
DTSTAMP:20250919T131511Z
DESCRIPTION:Title: Resolving the Replication Crisis Using Multilevel Modeli
 ng.\n\nAbstract: Andrew Gelman is a professor of statistics and political 
 science and director of the Applied Statistics Center at Columbia Universi
 ty. He has received the Outstanding Statistical Application award from the
  American Statistical Association\, the award for best article published i
 n the American Political Science Review\, and the Council of Presidents of
  Statistical Societies award for outstanding contributions by a person und
 er the age of 40. For more info\, please visit: http://www.stat.columbia.e
 du/~gelman/In recent years we have come to learn that many prominent studi
 es in social science and medicine\, conducted at leading research institut
 ions\, published in top journals\, and publicized in respected news outlet
 s\, do not and cannot be expected to replicate. Proposed solutions to the 
 replication crisis in science fall into three categories: altering procedu
 res and incentives\, improving design and data collection\, and improving 
 statistical analysis. We argue that progress in all three dimensions is ne
 cessary: new procedures and incentives will offer little benefit without b
 etter data\; more complex data structures require more elaborate analysis\
 ; and improved incentives are required for researchers to try new methods.
  We propose a way forward involving multilevel modeling\, and we discuss i
 n the context of applications in social research and public health.\n
DTSTART:20190322T170000Z
DTEND:20190322T180000Z
LOCATION:Room 25\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Andrew Gelman\, Columbia University
URL:/mathstat/channels/event/andrew-gelman-columbia-un
 iversity-295514
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