In modern test theory, differential item functioning (DIF) appears where respondents from two different groups have the same ability but different probability to respond to an item correctly. If some items favouring one group lead to the appearance of DIF in any other item favouring the other group, this type of problem is called artificial differential item functioning (A-DIF). The purpose of this paper is to deal with the effect of different factors causing A-DIF under the Rasch theoretical model for dichotomous responses. A simulation study was conducted to explore how various factors affect real DIF and simultaneous A-DIF expected proportion including total sample size, percentage of individuals in focal and reference groups, percentage of items exhibiting real DIF and DIF magnitude for two item sets including 10 and 20 items. It is concluded that DIF magnitude is the most essential factor while evaluating A-DIF for each item set. This is followed by percent of items exhibiting real-DIF.