*! version 1.0.0 05nov2017

Title

merlin reporting options -- Options affecting
reporting of results

Syntax

merlin models ..., ...
reporting_options

merlin, reporting_options

reporting_options

level(#) set confidence level; default is level(95)

coeflegend display coefficient legend

nocnsreport do not display constraints

noheader do not display header above parameter table

notable do not display parameter tables

eform display exponenitated coefficients

Description

These options control how merlin displays estimation results.

Options

level(#); see [R] estimation options.

coeflegend displays the legend that reveals how to specify estimated
coefficients in _b[] notation, which you are sometimes required to
type in specifying postestimation commands.

nocnsreport suppresses the display of the constraints.

noheader suppresses the header above the parameter table, the display
that reports the final log-likelihood value, number of observations, etc.

notable suppresses the parameter table.

eform display exponentiated coefficients for the main linear predictor

Remarks

Any of the above options may be specified when you fit the model or when you
redisplay results, which you do by specifying nothing but options after the
merlin command:

. merlin (...) (...), ...

(original output displayed)

. merlin

(output redisplayed)

. merlin, coeflegend

(coefficient-name table displayed)

. merlin

(output redisplayed)

Examples

Setup

. use http://fmwww.bc.edu/repec/bocode/s/stjm_pbc_example_data, clear

. merlin (logb time age trt time#M1[id]@1 M2[id]@1, family(gaussian))

Display coefficient legend

. merlin, coeflegend

Obtain 90 percent confidence intervals

. merlin, level(90)

Author

Michael J. Crowther

Red Door Analytics

Stockholm, Sweden

michael@reddooranalytics.se

References

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. Stata Journal 2020;20(4):763-784.

Crowther MJ. Multilevel mixed effects parametric survival analysis: Estimation, simulation and application. Stata Journal 2019;19(4):931-949.

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.

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;40(9):2139-2154.