Stata’s new stcrreg command fits competing-risks regression models. In a competing-risks model, subjects are at risk of failure because of two or more separate and possibly correlated causes. Existing command stcurve will now graph cumulative incidence functions after stcrreg.
Stata’s new multiple-imputation features may be used with stcox, streg, and stcrreg.
Factor variables may now be used with stcox, streg, and stcrreg.
Concerning predict:
predict after stcox offers three new diagnostic measures of influence: DFBETAs, likelihood displacement values, and LMAX statistics.
predict after stcox can now calculate diagnostic statistics basesurv(), basechazard(), basehc(), mgale(), effects(), esr(), schoenfeld(), and scaledsch(). Previously, you had to request these statistics when you fit the model by specifying the option with the stcox command. Now you obtain them by using predict after estimation. The options continue to work with stcox directly but are no longer documented.
predict after stcox and streg now produces subject-level residuals by default. Previously, record-level or partial results were produced, although there was an inconsistency. This affects multiple-record data only because there is no difference between subject-level and partial residuals in single-record data. This change affects predict’s options mgale, csnell, deviance, and scores after stcox (and new options ldisplace, lmax, and dfbeta, of course), and it affects mgale and deviance after streg. predict, deviance was the inconsistency; it always produced subject-level results.
For instance, in previous Stata versions you typed
. predict cs, csnell
to obtain partial Cox–Snell residuals. One statistic per record was produced. To obtain subject-level residuals, for which there is one per subject and which predict stored on each subject’s last record, you typed
. predict ccs, ccsnell
In Stata 11, when you type
. predict cs, csnell
you obtain the subject-level residual. To obtain the partial, you use the new partial option:
. predict cs, csnell partial
The same applies to all the other residuals. Concerning the inconsistency, partial deviances are now available.
Not affected is predict, scores after streg. Log-likelihood scores in parametric models are mathematically defined at the record level and are meaningful only if evaluated at that level.
Prior behavior is restored under version control.
New reporting options baselevels and allbaselevels control how base levels of factor variables are displayed in output tables. New reporting option noemptycells controls whether missing cells in interactions are displayed.
These new options are supported by estimation commands stcox, streg, and stcrreg, and by existing postestimation commands estat summarize and estat vce.
New reporting option noomitted controls whether covariates that are dropped because of collinearity are reported in output tables. By default, Stata now includes a line in estimation and related output tables for collinear covariates and marks those covariates as “(omitted)”. noomitted suppresses those lines.
noomitted is supported by estimation commands stcox, streg, and stcrreg, and by existing postestimation commands estat summarize and estat vce.
New option vsquish eliminates blank lines in estimation and related tables. Many output tables now set off factor variables and time-series–operated variables with a blank line. vsquish removes these lines.
vsquish is supported by estimation commands stcox, streg, and stcrreg, and by existing postestimation command estat summarize.
Estimation commands stcox, streg, and stcrreg support new option coeflegend to display the coefficients’ legend rather than the coefficient table. The legend shows how you would type a coefficient in an expression, in a test command, or in a constraint definition.
Estimation commands streg and stcrreg support new option nocnsreport to suppress reporting constraints.
stcox now allows up to 100 time-varying covariates as specified in option tvc(). The previous limit was 10.
Existing commands stcurve and estat phtest no longer require that you specify the appropriate options to stcox before using them. The commands automatically generate the statistics they require.
Existing epitab commands ir, cs, cc, and mhodds now treat missing categories of variables in by() consistently. By default, missing categories are now excluded from the computation. This may be overridden by specifying by()’s new option missing.
Existing command sts list has new option saving(), which creates a dataset containing the results.