In this situation, my guess is that you don't absolutely need
the -st- commands, but they could be tried out. I am fuzzy
about how bad it is to have some zeros.
I can't see that OLS -- or rather anything based on
an assumption of normal distributions -- is at all
attractive. Manifestly your response is constrained
to be zero or positive and right up against the limit of 0.
Alternatively, you could try fitting some non-normal
distribution directly, with and without your covariates.
Although some might be queasy about it, given
the nature of your data, -poisson-
might be a reasonable thing to try. More generally,
consider various kinds of -glm- or related commands.
Absent any censoring, what is best depends on what
kind of variability you have.
Nick
[email protected]
Christer Thrane
My dependent variable, gathered from a survey, is the variable "time
(measured in weeks) from from one started thinking about "X" until one
reached a decision about X." Also, everybody in the data reached this
decision. The data structure looks like this, and time ranges between 0 and
52 weeks (mean = 5.2 weeks):
id gender age time ...
1 0 30 7 ...
2 0 45 5 ...
3 1 36 0 ...
4 1 27 44 ...
and so on.
Q1: Is it theoretically meaningfull to think of this variable as suiteble
for survival analysis (SA), or is this "a job" for OLS regression
Q2: Provided that SA is meaningful, how should I set up the data in ths
instance?
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