The joint modeling of longitudinal and time-to-event data has exploded in the methodological literature in the past decade; however, the availability of software to implement the methods lags behind. The most common form of joint model assumes that the association between the survival and longitudinal...

Simulation studies are essential for understanding and evaluating both current and new statistical models. When simulating survival times, one often assumes an exponential or Weibull distribution for the baseline hazard function, with survival times generated using the method of Bender,...

The joint modeling of longitudinal and survival data has received remarkable attention in the methodological literature over the past decade; however, the availability of software to implement the methods lags behind. The most common form of joint model assumes that the association between the...

In medical research, particularly in the field of cancer, it is often important to evaluate the impact of treatments and other factors on a composite outcome based on survival and quality-of-life data, such as a Quality Adjusted Life Year (QALY). We present a Stata program, stiqsp, which...

Multilevel mixed-effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, or individual patient data meta-analyses, to investigate heterogeneity in baseline risk and treatment effects. I present the stmixed command for the...

I report briefly—and without giving away any Stata (or state) secrets—on my experiences as an intern at StataCorp earlier in 2012.

Simulation studies are conducted to assess novel and currently used methods in practice, to better assess and understand the frameworks under question. In survival analysis, we are interested in simulating both an event and a censoring distribution to better reflect clinical data. In this talk,...

Competing risks occur in survival analysis when a subject is at risk of more than one type of event. A classic example is when there is consideration of different causes of death. Interest may lie in the cause-specific hazard rates, which can be estimated using standard survival techniques by...

In population-based cancer studies, cure is said to occur when the mortality (hazard) rate in the diseased group of individuals returns to the same level as that expected in the general population. The cure fraction (the proportion of patients cured of disease) is of interest to patients and a...

Cure models can be used to simultaneously estimate the proportion of cancer patients who are eventually cured of their disease and the survival of those who remain "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be...