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In this paper count data with excess zeros and repeated observations per subject areevaluated. If the number of values observed for the zero event in the trial substantially exceedsthe expected number (derived from the Poisson or from the negative binomial distribution),then there is an excess of zeros. Hurdle and zero-inflated models with random effects areavailable in order to evaluate this type of data. In this paper both model approaches arepresented and are used for the evaluation of the number of visits to the feeder per cow perhour. Finally, for the analysis of the target trait a hurdle model with random effects basedon a negative binomial distribution was used. This analysis was derived from a detailedcomparison of models and was needed because of a simpler computer implementation. Forimproved interpretation of the results, the levels of the explanatory factors (for example,the classes of lactation) were not averaged in the link scale, but rather in the response scale.The deciding explanatory variables for the pattern of visiting activities in the 24-hour cycleare the milking and cleaning times at hours 4, 7, 12 and 20. The highly significant differencesin the visiting frequencies of cows of the first lactation and those of higher lactations wereexplained by competition for access to the feeder and thus to the feed

Generalized linear models with random effects for the description of data with excess zeros