Patterns of consumers' use of products are of interest to manufacturers. This paper is concerned with modelling diary data on the use of one product, shampoo, recorded to the nearest hour by over 500 men during 1 week. A binary response multilevel model is developed, building on similar models for consumer purchase data. The model allows for a dependence on the number of days since last use. The results of fitting various versions of this model are discussed. A problem is that the number of days since last use is missing for all times up to the first use. An approximate EM approach is considered to deal with this problem
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