On 13/01/2024 8:58 p.m., Rolf Turner wrote:
On Sat, 13 Jan 2024 17:59:16 -0500
Duncan Murdoch <murdoch.dun...@gmail.com> wrote:
<SNIP>
My guess is that one of the bootstrap samples had a different
selection of countries, so factor(Country) had different levels, and
that would really mess things up.
You'll need to decide how to handle that: If you are trying to
estimate the coefficient for Italy in a sample that contains no data
from Italy, what should the coefficient be?
Perhaps NA? Ben Bolker conjectured that boot() might be able to handle
this. Getting the NAs into the coefficients is a bit of a fag, but. I
tried:
My question was really intended as a statistical question. From a
statistical perspective, if I have a sampling scheme that sometimes
generates sample size 0, should my CI be (-Inf, Inf) for high enough
confidence level?
A Bayesian might say that inference should be entirely based on the
prior in the case of no relevant data. You could get similar numerical
results by adding some fake data to every bootstrap sample, e.g. a
single weighted observation for each country at your prior mean for that
country, with weight chosen to match the strength of the prior. But
Bayesian methods don't give confidence intervals, they give credible
intervals, and those aren't the same thing even if they are sometimes
numerically similar.
Duncan Murdoch
func <- function(data, idx) {
clyde <- coef(lm(Score~ Time + factor(Country),data=data))
ccc <- coef(lm(Score~ Time + factor(Country),data=data[idx,]))
urk <- rep(NA,length(clyde))
names(urk) <-names(clyde)
urk[names(ccc)] <- ccc
urk
}
It produced a result:
set.seed(42)
B= boot(e, func, R=1000)
B
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = e, statistic = func, R = 1000)
Bootstrap Statistics :
original bias std. error
t1* 609.62500 3.6204052 95.39452
t2* -54.81250 -1.6624704 36.32911
t3* -41.33333 -2.7337992 100.72113
t4* -96.00000 -1.0995718 99.78864
t5* -126.00000 -0.6548886 63.47076
t6* -26.33333 -1.6516683 87.80483
t7* -15.66667 -0.8391170 91.72467
t8* -21.66667 -5.4544013 83.69211
t9* 18.33333 -0.7711001 85.57278
However I have no idea if the result is correct, or even meaningful. I
have no idea what I'm doing. Just hammering and hoping. 😊️
<SNIP>
cheers,
Rolf
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