*! version 1.0.0

Title

multistate -- Multi-state survival analysis

Description

multistate provides a set of commands, described below, for multi-state survival analysis. This includes data
preparation tools, obtaining predictions from general continuous 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.

There are a number of commands in the multistate package, including:

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.

Website

Visit the multistate homepage for more information on tutorials,
short courses, and the package version history.

Authors

Michael J. Crowther (1,2,*), Micki Hill (3), Paul C. Lambert (2,3)

(1) Red Door Analytics AB, Stockholm, Sweden

(2) Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden

(3) Biostatistics Research Group, Department of Health Sciences, University of Leicester, UK

(*) michael@reddooranalytics.se

Please report any errors you may find.

References

Crowther MJ, Lambert PC. Parametric multi-state survival models: flexible modelling allowing transition-specific distributions with
application to estimating clinically useful measures of effect differences. Statistics in Medicine 2017;36(29):4719-4742.

Crowther MJ. Extended multivariate generalised linear and non-linear mixed effects models.
https://arxiv.org/abs/1710.02223

Crowther MJ. merlin - a unified framework for data analysis and methods development in Stata.
https://arxiv.org/abs/1806.01615

Weibull CE, Lambert PC, Eloranta S, Andersson TM-L, Dickman PW, Crowther MJ. A multi-state model incorporating
estimation of excess hazards and multiple time scales. Statistics in Medicine 2021; (In Press).