Item analysis data fitting the normal ogive model were simulated in order to investigate the problems encountered when applying the three-parameter logistic model. Binary item tests containing 10 and 35 items were created, and Monte Carlo methods simulated the responses of 2,000 and 500 examinees. Item parameters were obtained using Logist 5. Results indicated a substantial effect of the assumed third parameter on the other two estimated item parameters, if the estimation was made by molding the item characteristic function into the three parameter model when it actually followed the normal ogive model. This effect was stronger on the estimated item discrimination parameter than the difficulty parameter. Both of these parameters tended to be overestimated in order to counteract the effect of the guessing parameter. To amend these enhancements, the discrimination shrinkage factor and the difficulty reduction index were proposed. Results also indicated that tests must contain about 80 items in order to make good use of Logist 5. There was no substantial difference between 500 or 2,000 subjects. It was concluded that it may be dangerous to assume the validity of the three-parameter model, especially when test items are relatively easy. (GDC)