{smcl}
{* *! version 0.9 17may2013}{...}
{cmd:help ggtax}
{hline}
{title:Title}
{phang}
{bf:ggtax} {hline 2} Command for identifying your most suitable GG family model
{title:Syntax}
{p 8 17 2}
{cmd:ggtax}
{phang} {cmd:ggtax} is a postestimation command, see {manhelp postestimation_commands D} for help.
{title:Description}
{pstd}{cmd:ggtax} creates a graph for an easy interpretation of the shape and scale parameters of a
parametric survival regression with gamma distribution (see {manhelp streg D}).
{pstd}
When {cmd:ggtax} is ran after {bf:streg {it:varlist}, distribution(gamma)} it takes the shape and scale
parameters of the model and plots them with their respective confidence intervals
in the taxonomic map of hazard functions for the generalized gamma (GG) distribution (Cox, Schneider and Muñoz; 2007).
Each point in the map represents a different possible hazard function of the GG family.
{pstd}Reference lines are traced for the nested hazard functions of the GG family.
Ammag and Gamma reference lines divide the half-plane in four regions:
{phang}- Above Ammag and above Gamma (12 o'clock) the hazard function is bathtub-shaped.{p_end}
{phang}- Above Ammag and under Gamma (3 o'clock) the hazard function is decreasing.{p_end}
{phang}- Under Ammag and under Gamma (6 o'clock) the hazard function is arc-shaped.{p_end}
{phang}- Under Ammag and above Gamma (9 o'clock) the hazard function is increasing.{p_end}
{pstd}From the graph it can be easily ascertained which member of the GG familiy suits most:
{phang}- The model is GG if both Kappa CI and Sigma CI lines do not cross any reference line.{p_end}
{phang}- The model is standard Gamma, inverse Gamma, Ammag of inverse Ammag if the Kappa CI or Sigma CI lines cross with their respective reference lines{p_end}
{phang}- The model is Weibull or inverse Weibull if the Kappa CI line crosses with their respective reference lines{p_end}
{phang}- The model is Lognormal if the Kappa CI line crosses the Lognormal reference line (shape==0){p_end}
{phang}- If the circle lies in the intersection of Gamma and Ammag, the model is exponential{p_end}
{pstd}As far as version 12.1, Stata can parametrize the Lognormal, Exponential and Weibull functions of the GG family,
as well as the generalized Gamma model itself.
{pstd}If no gamma model is run before {cmd:ggtax}, it ends with an error.
{title:Reference}
{pstd}
Cox C, Chu H, Schneider MF, Muñoz A. Parametric survival analysis and taxonomy of hazard functions for the generalized gamma distribution.
Statistics in medicine. 2007 Oct 15;26(23):4352-74.
{title:Examples}
{bf:sysuse cancer}
{bf:stset studytime, failure(died)}
{bf:streg i.drug age, distribution(gamma)}
{bf:ggtax}
{bf:use http://www.stata-press.com/data/cggm3/hip2, clear}
{bf:streg protect age, distribution(gamma)}
{bf:ggtax}
{title:Acknowledgements}
{pstd}
This command is a tribute to Professor Álvaro Muñoz, in gratitude to his visit to Bogotá.
{title:Author}
{phang}Andrés González Rangel{p_end}
{phang}MD, MSc Clinical Epidemiology{p_end}
{phang}Instituto para la Evaluación de la Calidad y Atención en Salud - IECAS{p_end}
{phang}andres.gonzalez@iecas.org{p_end}