We present the Stata package stgenreg for the parametric analysis of survival data. Any user-defined hazard or log hazard function can be specified, with the model estimated using maximum likelihood utilizing numerical quadrature. Standard parametric models (for example, the Weibull proportional...

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...

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 paper demonstrates how cost-effectiveness decision analysis may be implemented from a Bayesian perspective, using Markov chain Monte Carlo simulation methods for both the synthesis of relevant evidence input into the model and the evaluation of the model itself. The desirable aspects of a...

There is an increasing need to establish whether health-care interventions are cost effective as well as clinically effective. It is becoming increasingly common for cost studies to be incorporated into clinical trials, either on all patients or more usually on a subset of patients. Establishing...

This article focuses on the modelling and prediction of costs due to disease accrued over time, to inform the planning of future services and budgets. It is well documented that the modelling of cost data is often problematic due to the distribution of such data; for example, strongly right...

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,...

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...