Posts Tagged ‘ AIC ’

R script to calculate QIC for Generalized Estimating Equation (GEE) Model Selection

March 23, 2012
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R script to calculate QIC for Generalized Estimating Equation (GEE) Model Selection

Generalized Estimating Equations (GEE) can be used to analyze longitudinal count data; that is, repeated counts taken from the same subject or site. This is often referred to as repeated measures data, but longitudinal data often has more repeated obse...

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R script to calculate QIC for Generalized Estimating Equation (GEE) Model Selection

March 23, 2012
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R script to calculate QIC for Generalized Estimating Equation (GEE) Model Selection

Generalized Estimating Equations (GEE) can be used to analyze longitudinal count data; that is, repeated counts taken from the same subject or site. This is often referred to as repeated measures data, but longitudinal data often has more repeated observations. … Continue reading →

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Montreal R Workshop: Likelihood Methods and Model Selection

March 16, 2012
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Montreal R Workshop: Likelihood Methods and Model Selection

Monday, March 19, 2012  14h-16h, Stewart Biology N4/17 Corey Chivers, McGill University Department of Biology This workshop will introduce participants to the likelihood principal and its utility in statistical inference.  By learning how to formalize models through their likelihood function, participants will learn how to confront these models with data in order to make statistical

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Bayesian modeling using WinBUGS

November 6, 2011
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Bayesian modeling using WinBUGS

Yes, yet another Bayesian textbook: Ioannis Ntzoufras’ Bayesian modeling using WinBUGS was published in 2009 and it got an honourable mention at the 2009 PROSE Award. (Nice acronym for a book award! All the mathematics books awarded that year were actually statistics books.) Bayesian modeling using WinBUGS is rather similar to the more recent Bayesian

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