Stata 15 help for xtstreg

[XT] xtstreg -- Random-effects parametric survival models

Syntax

xtstreg [indepvars] [if] [in] [weight], distribution(distname) [options]

options Description ------------------------------------------------------------------------- Model noconstant suppress constant term * distribution(distname) specify survival distribution time use accelerated failure-time metric offset(varname) include varname in model with coefficient constrained to 1 constraints(constraints) apply specified linear constraints collinear keep collinear variables

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

Reporting level(#) set confidence level; default is level(95) nohr do not report hazard ratios noshow do not show st setting information lrmodel perform the likelihood-ratio model test instead of the default Wald test nocnsreport do not display constraints tratio report time ratios display_options control columns and column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling

Integration intmethod(intmethod) integration method; intmethod may be mvaghermite (the default) or ghermite intpoints(#) use # quadrature points; default is intpoints(12) Maximization maximize_options control the maximization process; seldom used

startgrid(numlist) improve starting value of the random-intercept parameter by performing a grid search nodisplay suppress display the header and coefficients coeflegend display legend instead of statistics ------------------------------------------------------------------------- * distribution(distname) is required.

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 -------------------------------------------------------------------------

You must stset your data before using xtstreg; see [ST] stset. A panel variable must be specified; see xtset. indepvars may contain factor variables; see fvvarlist. varlist may contain time-series operators; see tsvarlist. by, fp, and statsby are allowed; see prefix. fweights, iweights, and pweights are allowed; see weight. Weights must be constant within panel. startgrid(), nodisplay, and coeflegend do not appear in the dialog box. See [XT] xtstreg postestimation for features available after estimation.

Menu

Statistics > Longitudinal/panel data > Survival models > Parametric survival models (RE)

Description

xtstreg fits random-effects parametric survival-time models. The conditional distribution of the response given the random effects is assumed to be an exponential, a Weibull, a lognormal, a loglogistic, or a gamma distribution. xtstreg can be used with single- or multiple-record st data.

Options

+-------+ ----+ Model +------------------------------------------------------------

noconstant; see [R] estimation options.

distribution(distname) specifies the survival model to be fit. distname is one of the following: exponential, loglogistic, llogistic, weibull, lognormal, lnormal, or gamma. This option is required.

time specifies that the model be fit in the accelerated failure-time metric rather than in the log relative-hazard metric. This option is valid only for the exponential and Weibull models because these are the only models that have both a proportional-hazards and an accelerated failure-time parameterization. Regardless of metric, the likelihood function is the same, and models are equally appropriate in either metric; it is just a matter of changing interpretation.

time must be specified at estimation.

offset(varname) specifies that varname be included in the fixed-effects portion of the model with the coefficient constrained to be 1.

constraints(constraints), collinear; see [R] estimation options.

+-----------+ ----+ SE/Robust +--------------------------------------------------------

vce(vcetype) specifies the type of standard error reported, which includes types that are derived from asymptotic theory (oim), that are robust to some kinds of misspecification (robust), and that allow for intragroup correlation (cluster clustvar); see [R] vce_option. If vce(robust) is specified, robust variances are clustered at the highest level in the multilevel model.

Specifying vce(robust) is equivalent to specifying vce(cluster panelvar); see xtstreg and the robust VCE estimator under Methods and formulas in [XT] xtstreg.

+-----------+ ----+ Reporting +--------------------------------------------------------

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

nohr, which may be specified at estimation or upon redisplaying results, specifies that coefficients rather than exponentiated coefficients be displayed, that is, that coefficients rather than hazard ratios be displayed. This option affects only how coefficients are displayed, not how they are estimated.

This option is valid only for the exponential and Weibull models because they have a natural proportional-hazards parameterization. These two models, by default, report hazards ratios (exponentiated coefficients).

noshow prevents xtstreg from showing the key st variables. This option is rarely used because most users type stset, show or stset, noshow to set once and for all whether they want to see these variables mentioned at the top of the output of every st command; see [ST] stset.

lrmodel, nocnsreport; see [R] estimation options.

tratio specifies that exponentiated coefficients, which are interpreted as time ratios, be displayed. tratio is appropriate only for the loglogistic, lognormal, and gamma models or for the exponential and Weibull models when fit in the accelerated failure-time metric.

tratio may be specified at estimation or upon replay.

display_options: noci, nopvalues, noomitted, vsquish, noemptycells, baselevels, allbaselevels, nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch; see [R] estimation options.

+-------------+ ----+ Integration +------------------------------------------------------

intmethod(intmethod), intpoints(#); see [R] estimation options.

+--------------+ ----+ Maximization +----------------------------------------------------- maximize_options: difficult, technique(algorithm_spec), iterate(#), [no]log, trace, gradient, showstep, hessian, showtolerance, tolerance(#), ltolerance(#), nrtolerance(#), nonrtolerance, and from(init_specs); see [R] maximize. These options are seldom used.

The following options are available with xtstreg but are not shown in the dialog box:

startgrid(numlist) performs a grid search to improve the starting value of the random-intercept parameter. No grid search is performed by default unless the starting value is found to be not feasible, in which case xtstreg runs startgrid(0.1 1 10) and chooses the value that works best. You may already be using a default form of startgrid() without knowing it. If you see xtstreg displaying Grid node 1, Grid node 2, ... following Grid node 0 in the iteration log, that is xtstreg doing a default search because the original starting value was not feasible.

nodisplay is for programmers. It suppresses the display of the header and the coefficients.

coeflegend; see [R] estimation options.

Examples

Setup . webuse catheter . xtset patient

Random-effects Weibull survival model . xtstreg age female, distribution(weibull)

Replay results, but display coefficients rather than hazard ratios . xtstreg, nohr

Stored results

xtstreg stores the following in e():

Scalars e(N) number of observations e(N_g) number of groups e(k) number of parameters e(k_eq) number of equations in e(b) e(k_eq_model) number of equations in overall model test e(k_dv) number of dependent variables e(df_m) model degrees of freedom e(ll) log likelihood e(N_clust) number of clusters e(chi2) chi-squared e(p) p-value for model test e(ll_c) log likelihood, comparison model e(chi2_c) chi-squared, comparison model e(sigma_u) panel-level standard deviation e(n_quad) number of quadrature points e(g_min) smallest group size e(g_avg) average group size e(g_max) largest group size e(rank) rank of e(V) e(ic) number of iterations e(rc) return code e(converged) 1 if converged, 0 otherwise

Macros e(cmd) gsem e(cmd2) xtstreg e(cmdline) command as typed e(depvar) _t e(wtype) weight type e(wexp) weight expression (first-level weights) e(covariates) list of covariates e(ivar) variable denoting groups e(model) model name e(title) title in estimation output e(distribution) distribution e(clustvar) name of cluster variable e(offset) offset e(intmethod) integration method e(chi2type) Wald; type of model chi-squared e(vce) vcetype specified in vce() e(vcetype) title used to label Std. Err. e(frm2) hazard or time e(opt) type of optimization e(which) max or min; whether optimizer is to perform maximization or minimization e(ml_method) type of ml method e(user) name of likelihood-evaluator program e(technique) maximization technique e(properties) b V e(predict) program used to implement predict e(marginsok) predictions allowed by margins e(marginsnotok) predictions disallowed by margins e(marginswexp) weight expression for margins e(marginsdefault) default predict() specification for margins e(asbalanced) factor variables fvset as asbalanced e(asobserved) factor variables fvset as asobserved

Matrices e(b) coefficient vector e(Cns) constraints matrix e(ilog) iteration log (up to 20 iterations) e(gradient) gradient vector e(V) variance-covariance matrix of the estimators e(V_modelbased) model-based variance

Functions e(sample) marks estimation sample


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