The "correct" CI for a binomial variable is a matter of dispute.
In your case you are looking for a CI around a point estimate of 0.029.
A symmetric CI around such a point estimate is likely to include 0
and some negative values unless the sample size is very, very large.
Some people just truncate the interval at 0, but a more defensible
procedure is to work on a transformed scale and back-transform, or do
something approximately equivalent that yields positive endpoints
for the CI with about the right coverage. [R] ci has several pointers
to the literature.
Alternative CIs can be got in this way:
. gen rep78_1 = rep78 == 1
. ci rep78_1 if rep78 < ., binomial jeffreys
. ci rep78_1 if rep78 < ., binomial Wilson
Nick
[email protected]
Martin Weiss
try this in Stata:
************************
sysuse auto, clear
proportion rep78
matrix define A=e(b)
matrix define B=e(V)
count if rep78!=.
*Upper/Lower Bound for proportion of "1"
di A[1,1]+invnormal(1-0.05/2)*sqrt(A[1,1]*(1-A[1,1])/`r(N)')
di A[1,1]-invnormal(1-0.05/2)*sqrt(A[1,1]*(1-A[1,1])/`r(N)')
*Standard Error for "1"
*Mistake obviously there...
di sqrt(A[1,1]*(1-A[1,1])/`r(N)')
************************
Then let me know: why do I not hit the correct CI for the proportion of
"1"
in the repair record? Something`s wrong with the standard error, I do
not
know what, though...
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
