Posts Tagged ‘ survival analysis ’

Example 9.7: New stuff in SAS 9.3– Frailty models

September 27, 2011
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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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Example 9.7: New stuff in SAS 9.3– Frailty models

September 27, 2011
By

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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Example 9.7: New stuff in SAS 9.3– Frailty models

September 27, 2011
By

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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Example 7.41: hazard function plotting

June 14, 2010
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Example 7.41: hazard function plotting

As we continue with our series on survival analysis, we demonstrate how to plot estimated (smoothed) hazard functions. RWe will utilize the routines available in the muhaz package. Background information on the methods can be found in K.R. Hess, D.M....
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Example 7.39: Nelson-Aalen estimate of cumulative hazard

May 31, 2010
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In our previous example, we demonstrated how to calculate the Kaplan-Meier estimate of the survival function for time to event data. A related quantity is the Nelson-Aalen estimate of cumulative hazard. In addition to summarizing the hazard incurred ...
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Example 7.38: Kaplan-Meier survival estimates

May 24, 2010
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In example 7.30 we demonstrated how to simulate data from a Cox proportional hazards model.In this and the next few entries, we expand upon support in R and SAS for survival (time-to-event) models. We'll start with a small, artificial dataset of 19 su...
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