`merlin`

~ **tutorials in Stata**

This page contains a collection of worked examples, specifically for the implementation in `Stata`

.
Examples are loosely grouped into areas, and may appear in more than one area.

Type `help merlin`

to access the help files, which document all the available options and utility functions.

If you have an example you’d like to contribute, then please get in touch.

Each tutorial below is tagged to illustrate the level of completeness, as follows:

- [Tutorial] - a completed page, with code and full worked example
- [Draft] - still in draft, contains code but not fully documented
- [Code only] - example code only, minimal description
- [Sim] - example shows how to simulate data from the illustrated model
- [TBA] - to be added
- [EG] - indicates that the tutorial shows how to fit an example from the literature within the
`merlin`

framework

*Things to read first:*

- Most importantly, have a look at the methods paper that introduces the modelling framework here

$~$

### Survival (time-to-event) analysis

- Using merlin with survival data [Tutorial, Sim]
- Parametric survival model with a frailty/random intercept [Draft]
- Parametric survival model with random coefficients [TBA]
- Three-level survival models - IPD meta-analysis of recurrent event data [Draft, Sim]
- Royston-Parmar multilevel survival models [TBA]
- User-defined hazard models - an example with fractional polynomials [Tutorial]
- Interval-censored survival analysis [Tutorial]
- Individual patient data network meta-analysis of survival data [TBA]

### Longitudinal (hierarchical) analysis

- Linear mixed effects model [TBA]
- Generalised linear mixed effects model [TBA]
- Mixed effects for the level 1 variance function [Tutorial, Sim, EG]
- Multivariate longitudinal model [TBA]
- Linear quantile mixed effects model [Tutorial, EG]

### Joint frailty models for recurrent and terminal events

- Joint frailty models for recurrent and terminal events [Tutorial, EG]
- General level joint frailty model [TBA]
- Joint frailty model with simple and complex time-dependent effects [TBA]

### Joint longitudinal-survival models

- Joint model with single continuous marker and survival [Draft]
- Joint longitudinal-survival model with time-dependent effects (non-proportional hazards) [Draft]
- Weighted cumulative joint longitudinal-survival model [Tutorial, EG]
- Multivariate longitudinal and survival model [Tutorial]
- Joint longitudinal and competing risks model [Tutorial, Sim]
- Generalised multivariate longitudinal and survival model [TBA]
- Generalised multivariate longitudinal and cause-specific competing risks model [TBA]
- Generalised multivariate longitudinal, recurrent event and a terminal event model [TBA]
- Generalised multivariate longitudinal and multi-state survival model [TBA]
- A trivariate model for joint longitudinal-survival data with an informative observation process [TBA, Sim, EG]

### Relative survival analysis

- An introduction to relative survival with
`merlin`

[Draft] - Relative survival model with a random intercept [TBA]
- Relative survival model with a random coefficients [TBA]
- General level relative survival model [TBA]
- General level relative survival model with time-dependent effects [TBA]

### Non-linear mixed effect models

- An exponential decay model [TBA]

### Meta-analysis

- Three-level survival models - IPD meta-analysis of recurrent event data [Draft, Sim]
- Individual patient data network meta-analysis of survival data [TBA, EG]

### Cost-effectiveness modelling

- A Gamma random effects model for costs [TBA]
- A two-part mixed effects model for costs [TBA, EG]
- A bivariate model for costs and utilities [TBA, EG]

### Miscellaneous

- A blog post on the importance of getting good starting values
- A blog post on modelling and prediction with non-linear effects