st.hlp

是一个经济学管理应用软件 很难找的 但是经济学学生又必须用到

{smcl}
{* 23mar2005}{...}
{cmd:help st}
{hline}

{title:Title}

{p2colset 5 16 18 2}{...}
{p2col :{hi:[ST] st} {hline 2}}Survival-time data{p_end}
{p2colreset}{...}


{title:Description}

{pstd}
The term st refers to survival-time data and the commands{hline 2}most of
which begin with the letters st{hline 2}for analyzing these data.  If you have
data on individual subjects with observations recording that this subject came
under observation at time t0 and that later, at t1, a failure or censoring was
observed, you have what we call survival-time data.

{pstd}
If you have subject-specific data, with observations recording not a span of
time, but measurements taken on the subject at that point in time, you
have what we call a snapshot dataset; see {helpb snapspan}.

{pstd}
If you have data on populations, with observations recording the number of
units under test at time t (subjects alive) and the number of subjects that
failed or were lost due to censoring, you have what we call count-time data;
see {help ct}.

{pstd}
The st commands are

{p2colset 9 27 29 2}{...}
{p2col :{helpb stset}}Declare data to be survival-time data{p_end}
{p2col :{helpb stdes}}Describe survival-time data{p_end}
{p2col :{helpb stsum}}Summarize survival-time data{p_end}
{p2col :{helpb stvary}}Report variables that vary over time{p_end}
{p2col :{helpb stfill}}Fill in by carrying forward values of
	covariates{p_end}
{p2col :{helpb stgen}}Generate variables reflecting entire
	histories{p_end}
{p2col :{helpb stsplit}}Split time-span records{p_end}
{p2col :{helpb stjoin}}Join time-span records{p_end}
{p2col :{helpb stbase}}Form baseline dataset{p_end}
{p2col :{helpb sts}}Generate, graph, list, and test the survivor
	and cumulative hazard functions{p_end}
{p2col :{helpb stir}}Report incidence-rate comparison{p_end}
{p2col :{helpb stci}}Confidence intervals for means and percentiles
	of survival time{p_end}
{p2col :{helpb strate}}Tabulate failure rate{p_end}
{p2col :{helpb stptime}}Calculate person-time{p_end}
{p2col :{helpb stmh}}Calculate rate ratios using Mantel-Haenszel
	method{p_end}
{p2col :{helpb stmc}}Calculate rate ratios using Mantel-Cox method{p_end}
{p2col :{helpb stcox}}Fit Cox proportional hazards model{p_end}
{p2col :{helpb estat concordance}}Calculate Harrell's C{p_end}
{p2col :{helpb estat phtest}}Test of Cox proportional-hazards assumption{p_end}
{p2col :{helpb stphplot}}Graphically assess the Cox 
        proportional-hazards assumption{p_end}
{p2col :{helpb stcoxkm}}Graphically assess the Cox 
        proportional-hazards assumption{p_end}
{p2col :{helpb streg}}Fit parametric survival models{p_end}
{p2col :{helpb stcurve}}Plot fitted survival, hazard, or
        cumulative hazard function{p_end}
{p2col :{helpb sttocc}}Convert survival-time data to case-control
	data{p_end}
{p2col :{helpb sttoct}}Convert survival-time data to count-time
	data{p_end}
{p2col :{helpb st_is:st_*}}Survival analysis subroutines for programmers{p_end}
{p2colreset}{...}

{pstd}
The st commands are used for analyzing time-to-absorbing-event (single-failure)
data and for analyzing time-to-be-repeated-event (multiple failure) data.

{pstd}
You begin an analysis by {cmd:stset}ting your data, which tells Stata the key
survival-time variables; see {helpb stset}.  Once you have {cmd:stset} your
data, you can use the other st commands.  If you {opt save} your data after
{cmd:stset}ting it, you will not have to {cmd:stset} it again in the future;
Stata will remember.


{title:Also see}

{psee}
Manual:  {bf:[ST] st}

{psee}
Online:  {helpb stset}; {help ct}, {helpb snapspan}
{p_end}