Posts Tagged ‘ survival analysis ’

Example 9.7: New stuff in SAS 9.3– Frailty models

September 27, 2011
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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...

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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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Example 7.39: Nelson-Aalen estimate of cumulative hazard

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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Example 7.38: Kaplan-Meier survival estimates

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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Example 7.30: Simulate censored survival data

March 30, 2010
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Example 7.30: Simulate censored survival data

To simulate survival data with censoring, we need to model the hazard functions for both time to event and time to censoring. We simulate both event times from a Weibull distribution with a scale parameter of 1 (this is equivalent to an exponential ra...

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