In group testing, the test unit consists of a group of individuals and each group is tested to classify units from a population as infected or non-infected or estimate the infection rate. If the test group is infected, one or more individuals in the group are presumed to be infected. It is assumed in group testing that classification of group as positive or negative is without error. But, the possibility of false negatives as a result of dilution effects happens often in practice, specially in many clinical researches. In this paper, dilution effect models in group testing are discussed and estimation methods of infection rate are proposed when a dilution effect exists.