Simulating Media Exposure Distributions

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We examine three media exposure distribution (e.d.) simulation methods. The first is based on the maximum likelihood estimate of an individual’s exposure, the second on ‘personal probability’ (Greene 1970) and the third on a dependent Bernoulli trials model (K’lotz 1973). The last method uses population exposure probabilities rather than individual exposure probabilities, thereby markedly reducing computation time. Magazine exposure data are used to compare the accuracy and computation times of the simulation methods with a log-linear e.d. model (Danaher 1988b) and the popular Metheringham. (1964) model based on the beta-binomial distribution (BBD). The results show that the simulation methods are not as accurate as the log-linear model but are more accurate than Metheringham’s model. However, all the simulation methods take less computation time than the log-linear model for schedules with more than six magazines, making them viable competitors for large schedule sizes.

Original languageEnglish
Pages (from-to)1381-1392
Number of pages12
JournalCommunications in Statistics - Simulation and Computation
Issue number4
Publication statusPublished - 1 Jan 1989
Externally publishedYes


  • dependent Bernoulli trials
  • media exposure distribution
  • personal probability
  • sim.ulation

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