Interval estimation for Poisson capture-recapture models in epidemiology
Related Experiment Video
Updated: Sep 29, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
1Department of Statistics, The Open University, Walton Hall, Milton Keynes MK7 6AA, UK. c.p.farrington@open.ac.uk
Abstract:
Capture-recapture studies in epidemiology are frequently undertaken to adjust underlying rates for underreporting. This contrasts with applications in ecology, in which the aim is to estimate population size. In consequence, the Poisson model provides a more appropriate framework than the multinomial in some epidemiological applications. A method for constructing profile Poisson likelihood interval estimates using log-linear modelling, avoiding the need for constrained optimization, is described for several relevant parameters, including the unobserved disease rate, the total disease rate, and the case ascertainment probability. Asymptotic properties of these estimates are studied and contrasted with those derived from the multinomial model. The method is illustrated with a published data set on spina bifida.
Related Concept Videos
Poisson Probability Distribution
The...
Statistical Methods for Analyzing Epidemiological Data
What are Populations and Communities?
Distributions to Estimate Population Parameter
Kaplan-Meier Approach
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
The...

