Goodness‐of‐fit based confidence intervals for estimates of the size of a closed population
- 1 July 1984
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 3 (3) , 287-291
- https://doi.org/10.1002/sim.4780030310
Abstract
Methods for estimating the size of a closed population often consist of fitting some model (e.g. a log‐linear model) to data with a missing cell corresponding to the members of the population missed by all reporting sources. Although the use of the asymptotic standard error is the usual method for forming confidence intervals for the population total, the sample sizes are not always large enough to produce valid confidence intervals. We propose a method for forming confidence intervals based upon changes in a goodness‐of‐fit statistic associated with changes in trial values of the population total.Keywords
This publication has 8 references indexed in Scilit:
- VALIDITY OF BERNOULLI CENSUS, LOG-LINEAR, AND TRUNCATED BINOMIAL MODELS FOR CORRECTING FOR UNDERESTIMATES IN PREVALENCE STUDIESAmerican Journal of Epidemiology, 1982
- Maximum Likelihood Applied to a Capture-Recapture ModelBiometrics, 1981
- USE OF BERNOULLI CENSUS AND LOG-LINEAR METHODS FOR ESTIMATING THE PREVALENCE OF SPINA BIFIDA IN LIVEBIRTHS AND THE COMPLETENESS OF VITAL RECORD REPORTS IN NEW YORK STATEAmerican Journal of Epidemiology, 1980
- Capture-recapture methods for assessing the completeness of case ascertainment when using multiple information sourcesJournal of Chronic Diseases, 1974
- Theoretical StatisticsPublished by Springer Nature ,1974
- A Probability Distribution Derived from the Binomial Distribution by Regarding the Probability of Success as Variable between the Sets of TrialsJournal of the Royal Statistical Society Series B: Statistical Methodology, 1948