RDA merlin

A unified framework for methods development and data analysis

merlin stands for Mixed Effects Regression for LInear, Non-linear and user-defined models.

merlin has the capabilities to fit a linear regression or a Weibull survival model, a three-level logistic mixed effects model, or a multivariate joint model of multiple longitudinal outcomes (of different types) and a recurrent event and survival with non-linear effects… the list is rather endless.

Installation

The latest stable version of merlin is available on the Statistical Software Components archive, and can be installed directly in Stata by typing:
Explore the range of user friendly wrapper functions

stmerlin

Survival analysis directly at your fingertips

stmixed

Multilevel mixed effects parametric survival models

morgana

Bayesian flexible survival models

Resources

Videos

State-of-the-art statistical models for modern HTA

At @RedDoorAnalytics, we develop methodology and software for efficient modelling of biomarkers, measured repeatedly over time, jointly with survival outcomes, which are being increasingly used in cancer settings. We have also developed methods and software for general non-Markov multi-state survival analysis, allowing for the development of more plausible natural history models, where patient history can […]
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Videos

Multilevel (hierarchical) survival models: Estimation, prediction, interpretation

Hierarchical time-to-event data is common across various research domains. In the medical field, for instance, patients are often nested within hospitals and regions, while in education, students are nested within schools. In these settings, the outcome is typically measured at the individual level, with covariates recorded at any level of the hierarchy. This hierarchical structure […]
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Statistical Primers

What are competing risks?

Competing risks In survival analysis, competing risks refer to the situation when an individual is at risk of experiencing an event that precludes the event under study to occur. Competing risks commonly occur in studies of cause-specific mortality, as all other causes of death than the one under study might happen before the individuals “have […]
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