Survival in STATA If you want to then use command. useful options (things you put after

the comma) Tell STATA you have a censored outcome with observation time obstime and event indicator

status

stset obstime, failure(status)

some exist in STATA, but you wont

need them currently

Graph a Kaplan-Meier Survival curve sts graph by(varname) allows you to graph separate survival curves on same plot

by level of varname gwood adds Greenwood 95% CIs around

the survival curve Graph a smoothed curve of the baseline

hazard function using kernel density estimation (based on the data, not any

model)

sts graph hazard makes a graph of baseline hazard instead of K-M survival curve cihazard adds confidence bands around

hazard function

List Kaplan-Meier survival estimates sts list by(varname) lists K-M survival estimates by levels of varname

Perform a logrank test of equality of survival functions

sts test varname wilcoxon allows you to do a Wilcoxon-Breslow test instead of a logrank test

Fit a Cox Proportional Hazards model stcox predictor list nohr gives estimated beta coefficients instead of hazard ratios

robust provides robust standard error estimates

cluster(id) lets STATA know you have dependent data by id

schoenfeld(varname*) stores Schoenfeld residuals for each observation in a

variable for each predictor in predictor list

scaledsch(varname*) stores scaled Schoenfeld residuals

mgale(varname) stores Martingale residuals for each observation

basesurv(varname) stores estimates of baseline survival in varname

basehc(varname) stores estimates of baseline hazard in varname

Test the Proportional Hazards assumption (after fitting a Cox model)

stphtest global test requires having specified schoenfeld() in stcox

individual tests require having specified scaledsch() in stcox

Plot a ln(-ln(S(t)) plot (after fitting a Cox model)

stphplot by(varname) specifies plotting by levels of varname

Plot survival predicted by Cox model with observed survival by Kaplan-Meier

stcoxkm by(varname) specifies plotting by levels of varname

Plot estimates of the hazard (survival) function at mean values of covariates (after

fitting a Cox model)

stcurve hazard is for plotting hazard function (requires basehc() option to have been

specified in stcox) survival is for plotting survival

function (requires basesurv() to have been specified in stcox)

at(varname=#) allows plotting of curve at covariate values specified by

varname=# at1(varname=#) allows you to plot

curve for another set of covariates on same plot as at()

range(startnum endnum) allows you to plot in a range between startnum and

endnum (useful for zooming in on plots to get survival estimates)

Plot Scaled Schoenfeld residuals vs. time and look for flatness of the smooth (flat smooth

implies PH is okay for that covariate, increasing or decreasing smooth implies

problems with PH)

lowess varname _t (here, varname is the stored scaled

Schoenfeld residuals corresponding to covariate you are checking for PH)

bwidth(#) allows bandwidth specification by a number #

(lower bandwidth makes curve try and fit each data point more)

Plot Martingale residuals for continuous covariates and look for shape of smooth (flat smooth implies functional form for covariate is okay, curved smooth implies transforming

covariate in the model)

lowess varname covariate (here, varname is the stored

Martingale residuals, covariate is a continuous covariate)

bwidth(#) allows bandwidth specification by a number #

mean uses running-mean smoothing instead of least-squares smoothing

(might want to do this when plotting Martingale residuals)