This paper presents a method for estimating certain characteristics of test items which are designed to measure ability, or knowledge, in a particular area. Under the assumption that ability parameters are sampled from a normal distribution, the EM algorithm is used to derive maximum likelihood estimates to item parameters of the two-parameter logistic item response curves. The observed information matrix is used to approximate the covariances of these estimates. Responses to a questionnaire on general arthritis knowledge are used to illustrate the procedure and simulated data are used to compare the actual versus estimated item parameters. A computational note is included to facilitate the extensive numerical work required to implement the procedure. (Author)