Computes a Wald confidence interval for an unknown population size using
mark-recapture sampling. This method assumes independence of the two
samples. This function requires the frequency counts from an incomplete
2 x 2 contingency table for the two samples (f11 is the unknown number
of people who were not observed in either sample). This method sets the
estimated odds ratio (with .5 added to each cell) to 1 and solves for
unobserved cell frequency. An approximate standard error is recovered
from the confidence interval.
Usage
ci.popsize(alpha, f00, f01, f10)
Arguments
- alpha
alpha level for 1-alpha confidence
- f00
number of people observed in both samples
- f01
number of people observed in first sample but not second sample
- f10
number of people observed in second sample but not first sample
Value
Returns a 1-row matrix. The columns are:
Estimate - estimate of the unknown population size
SE - recovered standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
Examples
ci.popsize(.05, 794, 710, 741)
#> Estimate SE LL UL
#> 2908 49.49071 2818 3012
# Should return:
# Estimate SE LL UL
# 2908 49.49071 2818 3012