Statistical Services Centre

Applied Statistics at the University of Reading
...making sense of statistics

Introduction to Capture-Recapture Techniques


This course will introduce capture-recapture techniques and models, and highlight their importance in the application fields of medicine and public health, and the life and social sciences. Such methods aim to address questions such as:

  • How complete is a register?
  • How many people have Type II diabetes (diagnosed and undiagnosed)?
  • How many people possess an illegal fire-arm?
  • How many illegal drug-users are there in a city?
  • How many medical professionals are alcohol-dependent?

Historically the purpose of capture-recapture (or mark-and-recapture) procedures was to determine the size of an unknown animal population. However, the methods may be applied more widely and may be used to estimate the size of a human population with a certain disease or a population which is difficult to approach such as a population involved in an illegal activity.

Day 1 of the course introduces the classical Lincoln-Petersen Estimation technique for the situation of two information sources such as hospitals or laboratories, if the characteristic of interest is a disease. Typically, registers, or more generally lists, are available and these are combined to provide a population size estimate. Extensions to more than two sources, leading to log-linear modelling, will be explained. Practical problems will also be discussed, along with the advantages of more than two sources. Practical work will be based around the use of Stata. The CARE software will also be considered.

Day 2 of the course introduces capture-recapture techniques in continuous time. Often recaptures arise not at fixed points in time but rather within a given time window. Typically, one source of information is used to repeatedly count the same individual, such as drug rehabilitation centres which record voluntary patient visits over time. Alternatively, when interest focuses on a criminal population, police data will allow the number of times an individual has been arrested to be counted. The course will explain how capture-recapture methodology can be applied in this context. In particular, a number of approaches which incorporate unobserved heterogeneity will be discussed. Practical work will make use of the SPADE software.

Who Should Attend?

The course is aimed at statisticians, biostatisticians, biometricians, epidemiologists, public health statisticians and social science researchers who have little or no knowledge of capture-recapture techniques.

How You Will Benefit

The course will develop your understanding of the huge potential of capture-recapture techniques.

What Do We Cover?

The course is divided into two one-day sessions.

Day 1:

  • Capture-Recapture based upon Multiple Sources
  • Introduction, datasets and case studies
  • The classical two-sources Lincoln-Petersen and Lincoln-Petersen-Chapman estimates; underlying assumptions and limitations
  • Variance and confidence interval estimation
  • Extensions to more than two sources: log-linear modelling and its advantages.

Day 2:

  • Capture-Recapture based upon Continuous-Time Experiments
  • Introduction, datasets and case studies
  • Capture-recapture and zero-truncated count distributions
  • Chao lower bounds
  • Zelterman upper bounds
  • Variance and confidence interval estimation
  • Related techniques.

Available Software

This course has practical exercises written for: CARE, SPADE, Stata

Extra Information

The practical exercises on Day 1 use Stata mostly, with CARE used at the appropriate stages. Day 2 exercises use SPADE.

Guest Lecturer: Day 2 of the course will be presented by Professor Dankmar Böhning of the School of Mathematics, University of Southampton.

Discounts: Participants can book for one or both days of this course. The cost for one individual day = £370.

Course Dates

24 - 25 September 2015

Duration: 2 days

Price: £695

An Academic discount is available for this course

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Page last updated: May 22 2015 16:16:49.