This paper surveys the techniques used in item re sponse theory to estimate the parameters of the item characteristic curves fitted to item response data. The major focus is on the joint maximum likelihood esti mation (JMLE) procedure, but alternative approaches are also examined. The literature shows that both the theoretical asymptotic properties and the empirical properties of the JMLE results are well-established. Al though alternative approaches are available, such as Bayesian estimation and marginal maximum likelihood estimation, they do not appear to have an overwhelm ing advantage over the JMLE procedure. However, the properties of these alternative techniques have not been thoroughly studied as yet. It is also clear that the properties of the item parameter estimation techniques are inextricably intertwined with the computer pro grams used to implement them.
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