Capture-Recapture analysis for 3 Sources with Goodness-of-Fit based confidence intervals ------------------------------
^recap var_freq var_A var_B var_C [if] [in]^
var_A: a variables with values 0 or 1, that desribes the belonging to list A var_B: a variables with values 0 or 1, that desribes the belonging to list B var_C: a variables with values 0 or 1, that desribes the belonging to list C
var_freq: a non-negative variable the describes the frequency of observat > ions in the combination of lists given by var_A, var_B and var_C. The u > nknown frequency of cases occuring in none of the lists is missing.
Description -----------
^recap^ provides an estimate of the total size of a certain well-defined population.
To apply this method you need three different sources containing members of this population, such that every member of the population has in principle the same change to be "captured" by a source. The model is flexible enough to allow dependences between the sources, such that an individual caught by source > 1 has a smaller probability to be caught by source 2.
An important point is that an individual that is present in two or three sources can be correctly identified. All in all there are eight possible situations: An individual can be present in all three sources, in two out of three, in one out of three or in none of them. By knowing the frequencies for seven of these eight possible combinations we can estimate the number of individuals that are captured by none of our sources.
To account for possible interactions between the three sources eight different models are compared in the analysis. The simplest one is the independent model, > then there are three models that allow for an interaction between two of the sources. More complicated are models with two pair-interactions present and the so called saturated Model, that adjusts for interaction between all three pairs > of sources. Note that all these models assume the absence of a triple interacti > on between the sources.
To compare the different models the Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC) are provided.
^recap^ also provides Goodness-of-Fit based 95% confidence intervals, see R.R. Regal and E.B. Hook "Goodness-of-Fit based confidence intervals for estimates of the size of a closed population", Statistics in Medicine, Vol. 3, 287-291 (1984).
Options -------
None.
Example -------
freq A B C ------------------- 5 1 1 1 15 1 0 1 3 0 1 1 20 0 0 1 7 1 1 0 37 1 0 0 14 0 1 0 . 0 0 0
. ^recap freq A B C^
calculates the capture-recapture estimates for this table.
Also see --------
Manual: [R] poisson Online: help for @poisson@