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Estimating the size of a population from a single sample: methodology and practical issues
1Statistical Sciences and Epidemiology Division, Nathan Kline Institute for Psychiatric Research, Orangeburg, New York, USA.
Journal of Clinical Epidemiology
|November 22, 1997
Summary
The Laska, Meisner, and Siegel (LMS) method estimates population size from a single survey. An enhanced LMS estimator significantly improves accuracy for population size estimation using limited data.
Area of Science:
- Biostatistics
- Population Dynamics
- Epidemiology
Background:
- Classical capture-recapture methods require multiple samples, limiting their application in certain scenarios.
- Estimating the size of a specific population, such as individuals served by a mental health center, often relies on efficient survey methods.
Purpose of the Study:
- To introduce and evaluate the Laska, Meisner, and Siegel (LMS) single-sample method for population size estimation.
- To present an improved LMS estimator that leverages additional information for enhanced accuracy.
Main Methods:
- The LMS method utilizes a single survey to estimate population size (N*) by ascertaining the time since last engagement in the defining activity.
- An improved LMS estimator was developed and assessed when supplementary data is available.
Main Results:
- The LMS method provides a viable alternative to traditional capture-recapture techniques using only one survey.
- The empirical assessment demonstrated that the extended LMS estimator offers substantial performance improvements over the standard LMS estimator.
Conclusions:
- The LMS method offers a practical approach for estimating population sizes from single surveys, particularly in fields like mental health services.
- The enhanced LMS estimator represents a significant advancement, providing more precise population size estimates when additional data can be incorporated.