We offer a range of user-friendly software packages in Stata, providing state-of-the-art statistical methods for use in practice
RDA SOFTWARE
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merlin
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.
multistate
multistate provides a set of commands, described below, for multi-state survival analysis. This includes data preparation tools, obtaining predictions from generalcontinuous time multi-state survival models, both Markov and semi-Markov, and plotting utilities. Transition hazard models must be estimated using the stmerlin or merlin commands.
survsim
survsim provides a cutting-edge framework for simulation of survival data. It allows simulation of survival data from a parametric distribution, a custom/user-defined distribution, from a fitted merlin model, from a specified cause-specific hazards competing risks model, or from a specified general multi-state model (with multiple timescales).
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Real-world evidence (RWE) Data and information that, unlike data generated in clinical trials conducted in controlled environments, has been obtained from everyday clinical practice, patient registers, or other sources outside the clinical trial setting. RWE plays a crucial role in complementing traditional clinical trial data, providing insights into the safety, effectiveness, and overall performance […]
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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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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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