We draw upon a series of articles in which a method based on pseu- dovalues is proposed for direct regression modeling of the survival function, the restricted mean, and the cumulative incidence function in competing risks with right-censored data. The models, once the pseudovalues have been...

In this article, we introduce the stthreg package of Stata commands to fit the threshold regression model, which is based on the first hitting time of a boundary by the sample path of a Wiener diffusion process and is well suited to applications involving time-to-event and survival data. The...

When the mortality among a cancer patient group returns to the same level as in the general population, that is, when the patients no longer experi- ence excess mortality, the patients still alive are considered “statistically cured”. Cure models can be used to estimate the cure proportion...

It is usual in time-to-event data to have more than one event of interest, for example, time to death from different causes. Competing risks models can be applied in these situations where events are considered mutually exclusive absorbing states. That is, we have some initial state—for...

Multilevel multiprocess hazard models are routinely used by demographers to control for endogeneity and selection effects. These models consist of multilevel proportional hazards equations, and possibly probit equations, with correlated random effects. Although Stata currently lacks a...

Simulation of realistic censored survival times is challenging. Most research studies use highly simplified models, such as the exponential, that do not adequately reflect the patterns of time to event and censoring seen in real datasets. In this article, I present a general method of simulating...

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 this article, I review Flexible Parametric Survival Analysis Using Stata: Beyond the Cox Model, by Patrick Royston and Paul C. Lambert (2011 [Stata Press]). Copyright 2013 by StataCorp LP.

We present the new laplace command for estimating Laplace regression, which models quantiles of a possibly censored outcome variable given covariates. We illustrate laplace with an example from a clinical trial on survival in patients with metastatic renal carcinoma. We also report the results...