ct.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}
{* 15mar2005}{...}
{cmd:help ct}
{hline}

{title:Title}

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


{title:Description}

{pstd}
The term ct refers to count-time data and the commands{hline 2}all of which
begin with the letters "ct"{hline 2}for analyzing them.  If you have data on
populations, whether people or generators, 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.

{pstd}
If, on the other hand, 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.  If you have survival-time data, see {help st}.

{pstd}
Do not confuse count-time data with counting-process data, which can be analyzed
using the st commands; see {help st}.

{pstd}
There are two ct commands:

{p 8 29 2}{helpb ctset} {space 5} Declare data to be count-time data{p_end}
{p 8 29 2}{helpb cttost} {space 4} Convert count-time data to survival-time data

{pstd}
The key is the {cmd:cttost} command.  Once you have converted your
count-time data to survival-time data, you can use the st commands to analyze
the data.  The entire process is as follows:

{phang2}1.  {cmd:ctset} your data so that Stata knows that they are count-time 
data; see {helpb ctset}.

{phang2}2.  Type {cmd:cttost} to convert your data to survival-time data; see 
{helpb cttost}. 

{phang2}3.  Use the st commands; see {help st}.


{title:Also see}

    Manual:  {bf:[ST] ct}

{psee}
Online:  {helpb ctset}, {helpb cttost}, {help st}
{p_end}