Stata 15 help for fmm_streg

[FMM] fmm: streg -- Finite mixtures of parametric survival models


Basic syntax

fmm #: streg [indepvars] [, options]

Full syntax

fmm # [if] [in] [weight] [, fmmopts]: streg [indepvars] [, options]

where # specifies the number of class models.

options Description ------------------------------------------------------------------------- Model noconstant suppress the constant term * distribution(distname) specify survival distribution time use accelerated failure-time metric offset(varname) include varname in model with coefficient constrained to 1 ------------------------------------------------------------------------- *distribution(distname) is required. You must stset your data before using fmm: streg; see [ST] stset. indepvars may contain factor variables; see fvvarlist. depvar and indepvars may contain time-series operators; see tsvarlist. For a detailed description of options, see Options in [ST] streg.

distname Description ------------------------------------------------------------------------- exponential exponential survival distribution loglogistic loglogistic survival distribution llogistic synonym for loglogistic weibull Weibull survival distribution lognormal lognormal survival distribution lnormal synonym for lognormal * gamma gamma survival distribution ------------------------------------------------------------------------- * fmm: streg uses the gamma survival distribution and not the generalized gamma distribution that is used by streg.

fmmopts Description ------------------------------------------------------------------------- Model lcinvariant(pclassname) specify parameters that are equal across classes; default is lcinvariant(none) lcprob(varlist) specify independent variables for class probabilities lclabel(name) name of the categorical latent variable; default is lclabel(Class) lcbase(#) base latent class constraints(constraints) apply specified linear constraints collinear keep collinear variables

SE/Robust vce(vcetype) vcetype may be oim, robust, or cluster clustvar

Reporting level(#) set confidence level; default is level(95) nocnsreport do not display constraints noheader do not display header above parameter table nodvheader do not display dependent variables information in the header notable do not display parameter table display_options control columns and column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling

Maximization maximize_options control the maximization process startvalues(svmethod) method for obtaining starting values; default is startvalues(factor) emopts(maxopts) control EM algorithm for improved starting values noestimate do not fit the model; show starting values instead

coeflegend display legend instead of statistics ------------------------------------------------------------------------- varlist may contain factor variables; see fvvarlist. by, statsby, and svy are allowed; see prefix. vce() and weights are not allowed with the svy prefix. fweights, iweights, and pweights are allowed; see weight. coeflegend does not appear in the dialog box. See [FMM] fmm postestimation for features available after estimation. For a detailed description of fmmopts, see Options in [FMM] fmm.

pclassname Description ------------------------------------------------------------------------- cons intercepts and cutpoints coef fixed coefficients errvar covariances of errors scale scaling parameters ------------------------------------------------------------------------- all all the above none none of the above; the default -------------------------------------------------------------------------


Statistics > FMM (finite mixture models) > Parametric survival regression


fmm: streg fits mixtures of parametric survival regression models; see [FMM] fmm and [ST] streg for details.


For a general introduction to finite mixture models, see [FMM] fmm intro. For general information about parametric survival models, see [ST] streg.


Setup . webuse lenses . stset t, failure(fail)

Cure model as a mixture of a point mass distribution at zero and a Weibull survival model . fmm: (pointmass fail) (streg inclength age10, distribution(weibull))

Stored results

See Stored results in [FMM] fmm.

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