RDA multistate

Flexible multi-state survival analysis at your fingertips

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. The package includes:

  • msset is a data preparation tool which converts a dataset from wide (one observation per subject, multiple time and status variables) to long (one observation for each transition of which a subject is at risk).
  • msboxes creates a descriptive plot of the multi-state process through the transition matrix and numbers at risk.
  • msaj calculates the non-parametric Aalen-Johansen estimates of transition probabilities, and the length of stay in each state.
  • predictms calculates a variety of predictions from a Markov or semi-Markov multi-state survival model, including transition probabilities, length of stay (restricted mean time in each state), the probability of ever visiting each state and transition specific hazard and survival functions. Predictions are made at user-specified covariate patterns. Differences and ratios of predictions across covariate patterns can also be calculated. Standardised (study population-averaged) predictions can be obtained. Confidence intervals for all quantities are available. User-defined predictions can also be calculated by providing a user-written Mata function, to provide complete flexibility. predictms can be used with a general transition matrix (cyclic or acyclic), and allows the use of transition-specific timescales.
  • graphms creates stacked transition probability plots, following a predictms call.
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Installation

The latest stable version of survsim is available on the Statistical Software Components archive, and can be installed directly in Stata by typing:
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stmt: Modelling multiple timescales using flexible parametric survival models in Stata

After many years of working on the stmt package in Stata, our paper Flexible parametric survival analysis with multiple timescales: Estimation and implementation using stmt was recently published in the Stata Journal (1). stmt can be installed by typing in Stata: ssc install stmt The aim of this paper was to describe and illustrate how to model multiple timescales using flexible […]
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