Forgot about this one -
On October 9, Rich Ulrich wrote:
>>>>>> Given a population of unemployed persons, i.e. names
>>>>>> and phone numbers. You wish to construct a histogram
>>>>>> of # of persons vs. time (# of days) out of work.
>>>>>> Stats 101, right?
>>>>>> Call some random subset of the list, ask them: when
>>>>>> were you laid off? Assuming the sample is unbiased,
>>>>>> it will satisfy the conditions.
>>>>> Well, the number represents what it represents.
>>>>> It is only a mis-report of you mis-report it.
>>> My position is that you can collect and report information for
>>> any numbers that might be interesting.
That's essentially the philosophy of science.
Every experiment is correct, in the sense that it is what it is. Start
with initial conditions, observe the results. Ask a question of nature,
she answers. She doesn't care about your confusion.
First, one must specify a hypothesis to be tested, and desired inference
to be drawn. One assesses experimental design correctness according
to whether the experiment meets these goals.
Let's recap: we want to learn the distribution of unemployed persons vs.
days out of work.
We are given a list of unemployed persons, i.e. names
and phone numbers. Presumably, the list is complete. We call
a sample, ask: how many days since you were you laid off?
Couldn't be simpler.
Later, perhaps, one might predict, probabilistically, how much time a
newly unemployed will require to find new work.
A reviewer objects. Those longer unemployed, will have a greater chance of
getting a call (or repeat calls). Therefore, the methodology is flawed; the
sample isn't unbiased. Hence the desired inference is invalid.
I find this objection spurious. Of course, the longer one is unemployed, the
greater chance of being sampled! That's inherent to the experiment, not a
defect. If Joe is out of work 100 days, the only question is whether he gets a
call, and whether 100 goes into the data. It doesn't matter if he was also
sampled 50 days ago.
The goal isn't to estimate the chance a person might receive a call, during
his lifetime, so to speak. That would be another hypothesis, another experiment.