Dennis Roberts wrote:
snip
but, we KNOW that most samples are drawn in a way that is WORSE than SRS ...
thus, essentially every CI ... is too narrow ... or, every test statistic
... t or F or whatever ... has a p value that is too LOW ...
what adjustment do we make for this basic
my previous remarks were about other sampling designs. I was comaring valid
complex designs to SRS design and not non-sampling case selection.
dennis roberts wrote:
my hypothesis of course is that more often than not ... in data collection
problems where sampling is involved AND inferences
most books talk about inferential statistics ... particularly those where
you take a sample ... find some statistic ... estimate some error term ...
then build a CI or test some null hypothesis ...
error in these cases is always assumed to be based on taking AT LEAST a
simple random sample
Hi, Dennis!
Yes, as you point out, most elementary textbooks treat only SRS
types of samples. But while (as you also point out) some more realistic
sampling methods entail larger sampling variance than SRS, some of them
have _smaller_ variance -- notably, stratified designs when the
and mccabe ... the stress throughout the book ... is on
SRSes ... and no real mention is made nor solutions to ... the problems
that it will be a rare day in analysis land ... for the typical person
working with data ... to be doing SRS sampling ...
it's just not going to happen
the bottom line, IMHO
Dennis Roberts wrote:
but, we KNOW that most samples are drawn in a way that is WORSE than SRS ...
thus, essentially every CI ... is too narrow ... or, every test statistic
... t or F or whatever ... has a p value that is too LOW ...
what adjustment do we make for this basic problem?
We
Dennis Roberts writes:
most books talk about inferential statistics ... particularly those
where you take a sample ... find some statistic ... estimate some error
term ... then build a CI or test some null hypothesis ...
error in these cases is always assumed to be based on taking AT
my hypothesis of course is that more often than not ... in data collection
problems where sampling is involved AND inferences are desired ... we goof
far more often ... than do a better than SRS job of sampling
1. i wonder if anyone has really taken a SRS of the literature ... maybe
