Rounding off our reports on major new developments in SAS 9.3, today we'll talk about proc mcmc and the random statement.Stand-alone packages for fitting very general Bayesian models using Markov chain Monte Carlo (MCMC) methods have been available for...

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Tags: Bayesian methods, clustering, JAGS, Markov Chain Monte Carlo, MCMC, OpenBUGS, proc genmod, proc mcmc, R2winbugs, random statement, rjags, WinBUGS

Posted in SAS | Comments Off on Example 9.8: New stuff in SAS 9.3– Bayesian random effects models in Proc MCMC

Rounding off our reports on major new developments in SAS 9.3, today we'll talk about proc mcmc and the random statement.Stand-alone packages for fitting very general Bayesian models using Markov chain Monte Carlo (MCMC) methods have been available for...

Read more »

Tags: Bayesian methods, clustering, JAGS, Markov Chain Monte Carlo, MCMC, OpenBUGS, proc genmod, proc mcmc, R2winbugs, random statement, rjags, WinBUGS

Posted in SAS | Comments Off on Example 9.8: New stuff in SAS 9.3– Bayesian random effects models in Proc MCMC

Rounding off our reports on major new developments in SAS 9.3, today we'll talk about proc mcmc and the random statement.Stand-alone packages for fitting very general Bayesian models using Markov chain Monte Carlo (MCMC) methods have been available for...

Read more »

Tags: Bayesian methods, clustering, JAGS, Markov Chain Monte Carlo, MCMC, OpenBUGS, proc genmod, proc mcmc, R2winbugs, random statement, rjags, WinBUGS

Posted in SAS | Comments Off on Example 9.8: New stuff in SAS 9.3– Bayesian random effects models in Proc MCMC

Shared frailty models are a way of allowing correlated observations into proportional hazards models. Briefly, instead of l_i(t) = l_0(t)e^(x_iB), we allow l_ij(t) = l_0(t)e^(x_ijB + g_i), where observations j are in clusters i, g_i is typically norma...

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Tags: Cox proportional hazards model, frailty models, proc phreg, random statement, simulate data, survival analysis, survival package

Posted in SAS | Comments Off on Example 9.7: New stuff in SAS 9.3– Frailty models

Shared frailty models are a way of allowing correlated observations into proportional hazards models. Briefly, instead of l_i(t) = l_0(t)e^(x_iB), we allow l_ij(t) = l_0(t)e^(x_ijB + g_i), where observations j are in clusters i, g_i is typically norma...

Read more »

Tags: Cox proportional hazards model, frailty models, proc phreg, random statement, simulate data, survival analysis, survival package

Posted in SAS | Comments Off on Example 9.7: New stuff in SAS 9.3– Frailty models

Shared frailty models are a way of allowing correlated observations into proportional hazards models. Briefly, instead of l_i(t) = l_0(t)e^(x_iB), we allow l_ij(t) = l_0(t)e^(x_ijB + g_i), where observations j are in clusters i, g_i is typically norma...

Read more »

Tags: Cox proportional hazards model, frailty models, proc phreg, random statement, simulate data, survival analysis, survival package

Posted in SAS | Comments Off on Example 9.7: New stuff in SAS 9.3– Frailty models