-stdmest-: Post-Estimation Predictions for Standardised Hierarchical Contrasts after -mestreg- and -uhtred- Models
-stdmest- is a Stata post-estimation command for hierarchical survival models fitted using -mestreg- or -uhtred-.
This command can be used to obtain predictions of, e.g., standardised survival probabilities while fixing posterior predictions of the random effects at any level of the hierarchy.
In other words, -stdmest- can obtain marginal predictions standardising across observed covariates (i.e., the fixed effects) while fixing predicted values of the random effects. Built-in post-estimation commands for -mestreg- and -uhtred- can do the opposite, i.e., marginalising over the random effects.
Three commands are provided by this package:
-
modexpt, to export results (e(b),e(V)) for fitted -mestreg- and -stmixed- models. This is useful to, e.g., use the R version ofstdmest, which is available here; -
stdmest, to perform regression standardisation while fixing random intercept values. Any number of random intercepts can be fixed using this command; -
stdmestm, to perform regression standardisation fixing one random intercept value while integrating over a second random intercept. For this, only three-level models (e.g., patients nested within surgeons, surgeons nested within hospitals) are supported.
The development version of -stdmest- can be installed from this GitHub repository by typing the following in your Stata console:
net install stdmest, from("https://raw.githubusercontent.com/RedDoorAnalytics/stdmest/main/")
- Gasparini, A., Crowther, M.J. & Schaffer, J.M. Standardized survival probabilities and contrasts between hierarchical units in multilevel survival models. BMC Med Res Methodol (2026). https://doi.org/10.1186/s12874-026-02782-8