In attitude measurement, questionnaires are often used to provide an efficient and objective way of getting information. Rating scales like Likert scales are often used to measure attitudes. In this project we will be especially interested in measuring attitudes and opinions through surveys. Both paper & pencil (P&P) data and data obtained by means of the computer are considered. In survey research, considerable attention has been given to response styles individuals exhibit when answering rating scales. Two response styles that are often mentioned are yeasaying/naysaying and "standard deviation". Other types of aberrant patterns are ''top-of-the-head'', inconsistent answers to questions with the same content and extreme response style. Several studies has been conducted to analyze the relationship between demographic and personality characteristics with respect to response styles, the effect of scale design on response styles and the effect of these response styles on attitude scores using multiple regression analysis with dummy variables. However, the use of IRT modeling has not been explored in this area. A major advantage of IRT models is that the goodness-of-fit of a model to empirical data can be investigated. Several IRT models have been specified that can be used to analyze rating scale data and several person-fit statistics have been proposed to analyze misfitting score patterns. In this project, the use of IRT models to aid related fit statistics to detect misfitting item score patterns in attitude measurement will be explored.